{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [In Depth: Linear Regression](05.06-Linear-Regression.ipynb) | [Contents](Index.ipynb) | [In-Depth: Decision Trees and Random Forests](05.08-Random-Forests.ipynb) >\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.07-Support-Vector-Machines.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open and Execute in Google Colaboratory\"></a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# In-Depth: Support Vector Machines\n",
    "\n",
    "# 深入：支持向量机"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Support vector machines (SVMs) are a particularly powerful and flexible class of supervised algorithms for both classification and regression.\n",
    "In this section, we will develop the intuition behind support vector machines and their use in classification problems.\n",
    "\n",
    "支持向量机（SVMs）是有监督学习算法中既能分类和回归的特别强大灵活的工具。本节中，我们会介绍支持向量机背后的机制以及它们在分类问题中的应用。\n",
    "\n",
    "> We begin with the standard imports:\n",
    "\n",
    "首先导入我们需要的包："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import stats\n",
    "\n",
    "# 设置Seaborn样式输出图表\n",
    "import seaborn as sns; sns.set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Motivating Support Vector Machines\n",
    "\n",
    "## 走进支持向量机"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> As part of our disussion of Bayesian classification (see [In Depth: Naive Bayes Classification](05.05-Naive-Bayes.ipynb)), we learned a simple model describing the distribution of each underlying class, and used these generative models to probabilistically determine labels for new points.\n",
    "That was an example of *generative classification*; here we will consider instead *discriminative classification*: rather than modeling each class, we simply find a line or curve (in two dimensions) or manifold (in multiple dimensions) that divides the classes from each other.\n",
    "\n",
    "在朴素贝叶斯分类中（参见[深入：朴素贝叶斯分类](05.05-Naive-Bayes.ipynb)），我们学习了描述每个底层分类的简单模型，和使用这些生成模型来预测新数据点的概率标签的方法。那是*生成分类*的一个例子；这里我们考虑不去使用*判别式分类*：与其对每个类别进行建模，我们试图简单的寻找到一条曲线（二维空间）或流形（多维空间）能将每个类别区分出来。\n",
    "\n",
    "> As an example of this, consider the simple case of a classification task, in which the two classes of points are well separated:\n",
    "\n",
    "作为一个例子，考虑下面的分类的简单任务，两种类别的点已经很好的分开了："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets.samples_generator import make_blobs\n",
    "X, y = make_blobs(n_samples=50, centers=2,\n",
    "                  random_state=0, cluster_std=0.60)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> A linear discriminative classifier would attempt to draw a straight line separating the two sets of data, and thereby create a model for classification.\n",
    "For two dimensional data like that shown here, this is a task we could do by hand.\n",
    "But immediately we see a problem: there is more than one possible dividing line that can perfectly discriminate between the two classes!\n",
    "\n",
    "一个线性判别分类器会试图在两个分类数据间画出一条直线，通过这样创建一个分类模型。对于像上面一样的二位数据，这个任务可以手工完成。但是我们立刻就会碰到问题：这里存在多条可能的直线能完美的划分两个分类。\n",
    "\n",
    "> We can draw them as follows:\n",
    "\n",
    "我们可以画出下面的直线："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xfit = np.linspace(-1, 3.5)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "plt.plot([0.6], [2.1], 'x', color='red', markeredgewidth=2, markersize=10)\n",
    "\n",
    "for m, b in [(1, 0.65), (0.5, 1.6), (-0.2, 2.9)]:\n",
    "    plt.plot(xfit, m * xfit + b, '-k')\n",
    "\n",
    "plt.xlim(-1, 3.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> These are three *very* different separators which, nevertheless, perfectly discriminate between these samples.\n",
    "Depending on which you choose, a new data point (e.g., the one marked by the \"X\" in this plot) will be assigned a different label!\n",
    "Evidently our simple intuition of \"drawing a line between classes\" is not enough, and we need to think a bit deeper.\n",
    "\n",
    "上图中有三条非常不同的分割线，但是都能完美的区分这些样本。取决于你选择了哪条直线，新数据点（例如图中标记为\"X\"的点）会被判定为不同的标签。显然简单的“画一条线分类”的简单直觉是不够的，我们需要更加深入地考虑这个问题。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Support Vector Machines: Maximizing the *Margin*\n",
    "\n",
    "## 支持向量机：最大化边缘\n",
    "\n",
    "> Support vector machines offer one way to improve on this.\n",
    "The intuition is this: rather than simply drawing a zero-width line between the classes, we can draw around each line a *margin* of some width, up to the nearest point.\n",
    "Here is an example of how this might look:\n",
    "\n",
    "支持向量机提供了一个方法来改进这个问题。这里的原理是：与其简单画一条0宽度的线来分类，我们可以每条线上画出一个有宽度的*边缘*，直至最近的点为止。下面是一个例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xfit = np.linspace(-1, 3.5)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "\n",
    "for m, b, d in [(1, 0.65, 0.33), (0.5, 1.6, 0.55), (-0.2, 2.9, 0.2)]:\n",
    "    yfit = m * xfit + b\n",
    "    plt.plot(xfit, yfit, '-k')\n",
    "    plt.fill_between(xfit, yfit - d, yfit + d, edgecolor='none',\n",
    "                     color='#AAAAAA', alpha=0.4)\n",
    "\n",
    "plt.xlim(-1, 3.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> In support vector machines, the line that maximizes this margin is the one we will choose as the optimal model.\n",
    "Support vector machines are an example of such a *maximum margin* estimator.\n",
    "\n",
    "在支持向量机中，拥有最大化边缘的线就是我们需要选择的那个最优化模型。支持向量机是这样的*最大化边缘*评估器。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fitting a support vector machine\n",
    "\n",
    "### 训练支持向量机\n",
    "\n",
    "> Let's see the result of an actual fit to this data: we will use Scikit-Learn's support vector classifier to train an SVM model on this data.\n",
    "For the time being, we will use a linear kernel and set the ``C`` parameter to a very large number (we'll discuss the meaning of these in more depth momentarily).\n",
    "\n",
    "下面我们来看看使用这个数据训练支持向量机模型的实际结果：我们会在这些数据上使用Scikit-Learn支持向量机分类器来训练一个SVM模型。目前我们先使用一个线性的核并且将`C`参数设置为非常大的数值（我们马上会深度讨论这些概念的含义）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=10000000000.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "    decision_function_shape='ovr', degree=3, gamma='auto_deprecated',\n",
       "    kernel='linear', max_iter=-1, probability=False, random_state=None,\n",
       "    shrinking=True, tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.svm import SVC # 支持向量分类器\n",
    "model = SVC(kernel='linear', C=1E10)\n",
    "model.fit(X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> To better visualize what's happening here, let's create a quick convenience function that will plot SVM decision boundaries for us:\n",
    "\n",
    "要更好的可视化展示这里发生的事情，我们创建一个快速的工具函数来绘制SVM的边界："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_svc_decision_function(model, ax=None, plot_support=True):\n",
    "    \"\"\"绘制2D SVC图像函数\"\"\"\n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "    xlim = ax.get_xlim()\n",
    "    ylim = ax.get_ylim()\n",
    "    \n",
    "    # 创建网格来展示数据\n",
    "    x = np.linspace(xlim[0], xlim[1], 30)\n",
    "    y = np.linspace(ylim[0], ylim[1], 30)\n",
    "    Y, X = np.meshgrid(y, x)\n",
    "    xy = np.vstack([X.ravel(), Y.ravel()]).T\n",
    "    P = model.decision_function(xy).reshape(X.shape)\n",
    "    \n",
    "    # 绘制边界和边缘\n",
    "    ax.contour(X, Y, P, colors='k',\n",
    "               levels=[-1, 0, 1], alpha=0.5,\n",
    "               linestyles=['--', '-', '--'])\n",
    "    \n",
    "    # 绘制支持向量\n",
    "    if plot_support:\n",
    "        ax.scatter(model.support_vectors_[:, 0],\n",
    "                   model.support_vectors_[:, 1],\n",
    "                   s=300, linewidth=1, facecolors='none');\n",
    "    ax.set_xlim(xlim)\n",
    "    ax.set_ylim(ylim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "plot_svc_decision_function(model);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This is the dividing line that maximizes the margin between the two sets of points.\n",
    "Notice that a few of the training points just touch the margin: they are indicated by the black circles in this figure.\n",
    "These points are the pivotal elements of this fit, and are known as the *support vectors*, and give the algorithm its name.\n",
    "In Scikit-Learn, the identity of these points are stored in the ``support_vectors_`` attribute of the classifier:\n",
    "\n",
    "这条分割线将连个分类之间的间隔最大化了。注意到其中某些点正好接触到边缘：可以看到上图中黑色虚线穿过的点。这些点是这个模型训练的关键元素，被称为*支持向量*，也是这个算法名称的由来。在Scikit-Learn中，这些点的数据被保存在分类器的`support_vectors_`属性中："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.44359863, 3.11530945],\n",
       "       [2.33812285, 3.43116792],\n",
       "       [2.06156753, 1.96918596]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.support_vectors_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> A key to this classifier's success is that for the fit, only the position of the support vectors matter; any points further from the margin which are on the correct side do not modify the fit!\n",
    "Technically, this is because these points do not contribute to the loss function used to fit the model, so their position and number do not matter so long as they do not cross the margin.\n",
    "\n",
    "这个分类器成功的关键是在拟合过程中，只有哪些支持向量的位置才有意义；任何其他超出边缘范围的点都不会改变训练结果。技术上来说，这是因为这些点并不会为损失函数提供任何贡献来拟合模型，所以它们不会通过边缘区域，它们的位置和数值没有意义。\n",
    "\n",
    "> We can see this, for example, if we plot the model learned from the first 60 points and first 120 points of this dataset:\n",
    "\n",
    "可以绘制这个模型通过前60个点的拟合结果以及前120个点的拟合结果来看到这一点："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mfPqZLe7MZl34LYUXnYdl1Sq01YqKRAgNH0HNXffJNRJtitK5v/vXHVheVlaDaeY8ljarY8dC1q2rznUY2zatsS5eiLF6FbFevTF79GzwlI3XQZVvoOTEoRi/rkD5/Yklmkrhv+ZvBMdcm4PgWx/rwm8pPuGYRL/42pZy2mpFFxVT/um0lAmfxvwueMZcjvN/r9fr2KIB7fFQPmMeZpft0/Z9tEXy9yj3DEPRvr0HoAewIrfRNEt3ZG6RF+T3OfNUdRXWuV+B1UZ0n/3A6ax3fNNr4HjjdQrHXIZGoUJBtMeTuJny1vuY3XvkIvxWx3PFxTjefQsjEKh7TLvdBEecjf+u+1K+bmu/C8bKPyg9aBBGTU29x02Xi/DJp1Hzn8daHnwbJ3+PcqspcwvZ7iFEtihFrN+eRI44OmmCYlOFl16IZdlSDL8fBahIBBUOU/Cf+7F98Xl24m3lPNdfnfj51SYoAFQshqqswH33nc0eV61di3Pya/USFEDddXJOeLLZYwshhBBNpQuLiA45gujgQxskKDZl+elHCsdcjgqFMEJBFGDU1GCsWU3x8FNk22IjWBctwPnOm/USFJAoZOp64TmMn39q9tjO8eNQSbrBGcEgztcnodZLC1nRdkiSQog8Y6xehX3Gl6hotMExFQzgfuyhHETVuqiqSqyLFiQ/Fo/jePetZo9tWzgfbXckHzsSwT71s60PUlOD9Zt5WH76sdlxCCGEEE3hfPopiCWZW5gmxppVWOfNyUFUrYv9nbcgHE5+0IzjeO/d5o/9xedJkxQA2u7AtuCbrY5hrFiO9Zt5qKrKZschRD6QJIUQecb49Ve0I/mHYADLT8uyGE0rFYuRWNuQnIrHmj209hSCNlMfLy5O/eJ4nIJ/3kKHvjtTfNqJlA45iNIDBmBd+G2z4xFCCCEaw7rkB1Qs1fufwrL856zG0xqpcBjMFHOAeBwVTZ5kaAxdlLpbC9rE9KQ+blnqo2TIgbQbvB/Fp51I+913wXP9XyHJDS8hWgNJUgiRZ8wddkCFU7/JxWXP6Fbp0nbEuyYvjqmVInLAwc0eOzpoX3AkX05rugsInXN+ytcW3HYzrqfHo4JBjOoqVDCIddmPFJ94LMZvvzY7JiGEEGJr4rv0RltT18yP79g9e8G0UpEhh6MLCpIfdDqJHHJYs8cOnXN+ypb1OF3EBg5KekitX0/J0COwfrcYFaqdX4RCOF99Gc+YK5odjxC5JEkKIfKM2WV7ovvuh7Y2rOKs3W4CV/xfDqJqZZTC/6+7E/3hN+d0Efj7rc0f22KhatzTaJcLbbHUPWy63UT3P4DwcSckD6myAtdzT6OCgYbHwmFc46QglhBCiMwJXnAxJJtbKIVu357YvvvlIKrWJXrwIcR7exuseNVOJ9H+A4ntPaDZY4ePP4novvvXS1RoiwXtclE17mnYZM6xKefzz6DCIdRmNUVUKIjz7TcwVq1sdkxC5IokKYTIQ1VPPE18p50wCzwAaKsN7XQSuPhyokOOyHF0rUPkqGMSP8cddkQ7nGi7ndhufan471stbhMaPeQwyj/6gtAppxPv3oPoXv2puedBql6YlHISYV28CG23Jz2molHsnzeiloUQQgjRTPHeXqrveTDxnlj7Idss8KA7dKDy1Tda3D6zVdAa69yvcD32MM6JT6PWrWva6w2DisnvEjrptMTP0eVGu1yEho+k8qX/tuxnaLFQ9dJ/qbn7AaJ79SfevQehU8+g/OMvE0VRU3B89gkqFEp6TNvsWOfNbX5MQuRI6jVfQoic0R07Uj59LvZPPsI2czq6uJjQiadg9tw516G1KpFjj2PDMUMx1qxOJHo6dEjb2HHvrtQ81vhOHrqgAOLx1McLC9MRlhBCCJFS+MyRRIf8Bcfk1zBWrya2516JFYBbqIW1rVBVlRSfcTKWH75HRSJomxXPLTdQc/PthC6+rPEDeTzUPPI4NXffj7GhDLNDxy12VWkSq5Xw8JGEh49s9EvMLdWyUIn26EK0NmlLUni93hVAqPYfwN98Pt+H6RpfiDbHYiFy1DFEjjom15G0bkphdu6S6yiI7bFXouim39/gmOl2Exp1Xg6iEiL/yfxCZFQ8jqqoSCSKU6x229aYnToTvOyqXIeRdYVXXoJ10YK6DhqqttOJ567bie/ej+iBTaxX5XanriGRRaGR52CbOQMj0HB+gVJN/76EyAPpXklxqs/nW5zmMYUQovUzDKofH0/xWadDJIKqXVVhulzEd9+D0GnDcxygEHlN5hciveJx3A/ei+vJx1HhEChF6OTT8P/r3+jCLdyZFq2SWrsW+2efJG/xGQzifuRBKlvph/nI0ccSPeBAbDOnYwQSda+0YYDDQfUj49pM8k1sW2S7hxBCZEn04EMo/+gL3A/dj232THRREcFzLyA08hyZRAghRDqZJta5czDWria+627Ed+ld77DnqktxvPsWRjBY95jz9UlYv51PxSdfwha6YIjWx/LrCrTdkWghuhkFWH5cmv2g0sVioeqFSTheewXXhHEYGzYQ23sAgTHXENtjr1xHJ0SzpPsv8Eter1cB04GbfD5fRZrHF0KIVi3u3ZXqJybkOgwhWhuZX4hGsy78lqJRZ6IqK8FQqGiM6N79qZr4Erq0Hcbyn3G+/WZiBcUmVCSC5ZcV2D98n8jQYTmKXmSC2WV7VKRhgmKjeLcdshhNBlgshM88i/CZZ+U6EiHSQunN2tU0l9fr3cHn8/3m9XodwENAoc/na8xvSndgeVqCEGJbV1MDf/wBnTpBSUmuoxFCbPt6ACtyGUAz5xfdkblF21RWBj17QlVV/cftdujfH2bNgnHj4OqrYZNVFPWcfTY8/3zmY80nv/0GkQj06AHGNtr875BDYMaMhkWsCwrgpZfghOQtxIUQabfVuUXaVlL4fL7fav837PV6Hwfebsrry8pqMM30JExE03XsWMi6ddUtHketW0fBvXfi+N/rqHCY6KD98N90C7GB+6Qhym1fyusQCOC56Tqcb/wXbbGiYlEiRxxN9YOPoEtKsx/oNixdvwui+eQa5J5hKNq3z4+K8C2ZX8jcIvfS9fts//gD3HffiXXpErSnkOBZ5xAYc23iA+YmXI+OxR2J0OBjdiSCXrCQis+mYw1EKUA1fA6ggVBMU7MN/Q3a0jWwzZ6J5+orsfz2G1gMzAIP/tvvJHzqGVmOMvOMx8ZTMvQI1IYNGP4atMUCNjvBkaPw738YZPia5+V7m2liXfgtKhgk1m+PRIHvbVheXoM2pClzi7QkKbxebwFg9fl8lbXLMYcD36ZjbNF6qLIySv9yEMb69XUVk23Tv6DklDlUPvcK0UOH5DjC1qv4rNOxzp2DCofY2IHb/uH7lAw7mvKpM8FiyWl8QgiRCTK/EADO557Gc+vfUcFEUUAVDuMaNxb7px9T8f6n9dpn2mbPxAiFko6jFVgXLiByxFF4brou+XMKCgifdGr6v4k8ZF20gOIzTkJtsqLEEghQeM1VYBiETz4th9Gln9m5CxtmfYPjvXewfTkVXVxC6LThxHfrm+vQQGssPy+DuEm81y5ZWc1i+/xTCq+8BOX3g2GgolECF19G4KZbQamtDyBEBqXrN6ATMNXr9S4EFgO9gSY0HBbbAtfjj2BsKKtLUECiGJEKBhNveGnaWtTWWOd/jfWbeRib752NRjB+/w37x9KJTwixzZL5RVsXCFDwjz8TFBsZ4RCWn3/C8ebkeo+bnTonOhskYxiY7dpjdu5C4KJLG7SP1E4Xsf4DiQ4+NJ3fQd5y//tfkCSho4JBCm6/Zduct9nthE88hZoHH8X/j3/lRYLC/vEHtNu7D6V/OZiSIw+lXb/eOP43eesvbAHrogUUnzsCy9o1GP4ajOoqVCiI66kncD1wb0bPLURjpGUlhc/n+xnYOx1jidbLOfm15K2dAGP9eizLfyLes1eWo2r9bNOnpf65+muwf/YxkaOPzXJUQgiReTK/EPaZ01KuFjQCfpyTXiZ8xoi6x0Jnn4tz8mvJ600oRWTI4QAEbr6deO9dcT94L5bffsUsLSV4wSUEr/i/bbcmw2Zss2agUiQijPINGKtXYXbZPstRtS22GdMoGn1O3WoWBRDwUzjmMrTLlbH5nfuBe5MmqIxgAPfYhxO/B05nRs4tRGO0jb/CIjtisZSHtKEgmvp4a6XWrMH22SdY53+duTsOTgdYkucTtWGg3QVJjwkhhBCt3lbmDpsn8WN7DyAw+hJMtxtdu2Rd22xol5uq8c/9uTVEKcJnjKD8q29Zv3IDG777ieDV1+VHO2itsX4zD9tnn6DWrs3ceWxb+F5NE73JNhqRGQX/+ke97TYbJVaz3Jyx89rmzE6ZoEKBZfnPGTu3EI0hSQqRNpEjj0an6ivucCb22G0rQiEKLx1N+4G7U3ThuRSffBzt9u6Dde5XaT9V+NgttEFzOAif3Db2zgohhGh7ovvtj4pEkx7TTieh409q8HjgltupevUNwsefRHTgPgTPG82GL2YRrV1Fkc+sc76i3V59KD5lGEUXnkv7AX0pvPRCCKdun9lc4ZNPRdtsSY/Fdu+Hbtc+7ecU9Vm//SblMcuK5eD3Z+S8pid18UIVi6GLijJyXiEaS5IUIm0CY65Fu1xsnpfd+LWxfl22Q8qYwv+7DMeUt1HhMEZ1FYbfj2XlSopPPxHjt1/Tei6zazcCl12JdtXfO2u63YROOIXYHnul9XxCCCFEvtCl7QhedCl6s6XnGiAUSrnSILrfAVSPn0jFe5/gv+MezO49Mh9sCxm//kLxGSdiWbUSw+9P1AkIh3FMeZvCMZen/Xz+a27AbN8evcmKCm2xYBYUUHPfQ2k/n0hiS6tZlIIUSaSWCp1zPtrlavC4BmK9emN27ZaR8wrRWJKkEGlj7rgT/utvbrCXUwGqqpLCSy7ITWBpZqxeheO9d1DJik1ForjGj0v7OQM33kLV2KeI7rk3ZnExMW8fau5+gJqHx9Z7nnXhtxT8/Xo8l1+M47VXku43FEIIIVoT/823YRYV17sJomr/FYx/AtusGTmKLL1cTz2etAaVCgVxvPsWas2atJ5Pd+xI+WczCY6+iPh2nTBL2xE+8RQqPvmSWL89/3xiIIDzpefxXHYhBbfciOW7xWmNoy0LH39iohXqZrRhEDlkSMa2HwXPv4jYLl7MTRIV2mZHFxZS/diTGTmnEE2RlsKZQmzkeHsyyjQbPK5iMWzz5mKsWpn9IkzxOI533sQ58WmMigoiBw0meMnlmN12aNZw1kUL0HYHKsnSSxWNYJsxraURJxU57ngixx2f/KDWeG64BuerL0E4jDJNHO+9TcGdt1Px/qeY23fNSEwtVlOD5fffMNt3QHfsmOtohBAi++JxjFUr0R4PuqQ019HkJcsP32PUVJO0KWIoiGvcWKL7H5jtsDD++B3XU49j/2IqZnExoXMvIHz8Sc1uC26fMR0VTbG1xe7AtngBkU5HtiTkhuN26ID/9rvw335X0uPG8p8pPe4I8AcwAn60xYLruWcIXHQpgZtvS2ss6WT8/hsqECDeo2fGViOkg//m27B//ilUVqKiiQSVtlrRBR5q7rwncyd2uah49yOck17G+cJEVCBA5PAjE/PjfJ0zijZFkhQirSx//JHymHbYs5+kiMcpOvsMbDOnYwQS7cssPy7F+dJzVE5+h1j/gU0e0iwuhSSJmI10++zv4bS/9y6OSS/XK75k+P3oUIjCi86j8t2Psh7TFkUieG65AecrL6GtVlQ0QnTf/al+7EnMzl1yHZ0QQmSe1jgnPEnB/XejQkGIxYkOHETNfx6VTlibsaz8PfFekeSY0hrLLyuyHRLWb7+h+OTjUOFI3YdL64L5OCa9TNWLr0GqGl1bYLZrt4WDJmZxSXPDbUBVVeJ47VVsX88j3qUL4ZFnE9+5Ye2w4nNHosrK6m5AqXgc4kHcE8YRHXxo3rVrtX77DYVXXYpl+XK01QIWK/7rbyJ04SWJ7RN5xuyyPRumzsI99iEcb74Bpklk6DACV/4181sunE5C55xP6JzzM3seIZpBtnuItIrv0rtBTYqNVDhMfMfu2QwHx/9er5eggMRqB8Pvp+ii85rVkSM2cBC6IHlHDdNdQPCc7G9rcVxgETMAACAASURBVI17rN73uJGKx7Et/DbtdTJaquiSC3C+8hIqFEzcHQuHsc2YRslRh0GS70MIIbY1rocfpODO2zDKN6CCwcRKvNkzKTlqSNqX9bd2sZ69Urbi1oZBbLe+2Q1Ia4ouOg+jpqYuQQFgBALYZs/EMfm1Zg0bPHc02u1Oekx7PM26sZKMZfEi2g3YnYI7/oFz8iTc48ZSetiBOMfV30JqWfIDlhXLk66QJRDA9eTYho/nkOXnZRSfNBTrkh9Q4VCirkdVJQV33o5r3GO5Di8lvd12+G+/iw0LlrBh0VJq7n5AakKINk+SFCKtAlddDa6Gb7DabidyxFHoDh2yGo/rmfFJP7wDqPXrm7ev0jCoHj8R7XbXq4ptuguIDvkLkWOGNjfcZrP88XvKY9pux1i9KovRbJnx80/YP/kwcedwEyoeR1VW4vzf6zmKTAghsiQQwP3QfQ3en5TWqGAA1/gnchRYfjJ77kx0r/7JO1E4HAQuvTKr8Vh++B61NnkiyQgEcD07oVnjRoYOI3LokHqtxbXNhnbXtk810jBtN02KR5yKqqys++9PxaKoUAjPv/+JZfGiuqcaK/9A25KvCFGAJc9ugLj+80DSemFGMID7/nsgRaJLCJF/JEkh0ip68CHU3HgL2uFI9CivfXON7bk31Y9kaNIVi+F68nHaDdidDjt1puSwA7C/8xYAqrw89eusFoyKLRzfguj+B7Jh6ixCo84jtltfIgcNpvrRcVRNeD49k4gmiu3aZ8srWLr3zGo8W2KfPROd4mdkBPzYP3wvyxEJIUR2WRcuSFm3QEUiON57N8sR5b+qZ14kvktvzIICtNWWmGM4nVTf9xDxfntk5JyWH5dSOPoc2u/clfa77IDnr1dgrPwDo7Jii9s5VPmG5p3QMKh65kWqHn2CyEGDie3Wl+Co89kwdRax/fZv5ndRn23WDFSq+h6RCK5nnqr7Mt5rF1R4CytY+vZLS0zpYv/is8R2lGS0iWWpL7sBCSGaTWpSiLQLXXI54VNOT7To9PuJ7rd/YoliJvYCak3ROWdimz4NI5i4I2D7bjFFV1yMf+kSovsfgOWX5ahYrMFLVTjSoiWiZvce1Pz7/ma/Pp2CV12NfcY0CNZfnVC3giWPilJqpzNlIkcD2lOY3YCEECLb7LYtbzd0OLIXSyuhO3Sg/POZ2GbNwPrN1+jSUsJDh2Ws2Khl8SJKhh2Z2IpTu93BOellHO+9S8X/3k394d1iaVkRT8MgMuxEIsNObP4YWxp+5R8p/9tT8TiWFcvrvjZ33InovvthmzWz3rYWABwOgpdldwXLVm3WpnZTKh4Hd8OWm0KI/CQrKdqyUAjnxAmUHD4Y+val4LabMVatTMvQumNHQudeQPDyq4gNGJSxYkW26V9imzG9LkGxkQoGKHjofoIjzk7avkk7XYROOwPdLvtFLjMhut8B1Nx+558rWOx2tMtNtP/AzK1gaabIX45ImjQCwF1A6IwR2Q1ICCGyLLbn3mBPnojQLhehM0dmOaL0sviW4LnyUkoPGACDB2N/+38NC07H4xi//oJav77xAytF9ICDCF7xf4RGjspoNxTPDdeg/P569RhULIaqqsT92MOEho+o176xjt1B8IoxGYurpeK79EalSFJom53YHnvWe6xq/ERifXarm1uY7oLECpb7H67fpjQPBIePxEyRqIh37kK8x85ZjkgI0VyykqKtCgQoGXYUlmVLMWrvvruWLcP54kQq3v2Y+K59chxg4zgmv4YK+JMe0xYrNt8SKl/6L4UXn4/y+8EwUJEwoZNOoeaeB7McbYLlh+9xP/wAtjmzMUtKCJ1/UeKDeQtbZIXOHU34hJNxvD8FVV1FdN/9ie3VP01Rp48uLqHm9rvw3HYzapPkkna7iRySf5XChRAi7SwWqh98lKJLL6jXlUk7HMS77UBw5Dk5DK5l7J9+RNH5Z0Mkkrh7vexHir7+mvA7b1H91LMAOJ8ZT8G9d0E4hIrFiO2xJ9UPPpY/c4+aGmzfzEveTSQexzHlbdYv+x1iMZyvT0LbHaBNtMtN9ZPPEO/VsEtGxsViOF97BefTT2KUlxMdtC+B/7uG+GYrRmN77k28e08sS5c0vGFgtRA878J6D+nSdlR8/AXWeXOwfTMPs7iEyLHHoYuKM/0dNVnooktx/vdV1O+/1bWJ14YBDifVDz+Rl909hBDJKd2M7gZp1h1YXlZWg2nmPJY2w/XwAxQ8cE+DAkNaKWJ77k3FR1NzE1gTFV56Ac7J/016zHQ68d9+F6HzRoNpYv1mHqqqili/PXO2/cH2+acUnzsyMTGrvTuj3W6iAwZROel/dOxSyrp11TmJLdtsX07F/eC9WJd8j9lhO4IXXUpo5Khm95dPl44dC9vMNchXcg1yzzAU7dt7AHoAK3IbTbN0pxXMLaxfzabgnjuwzv8a3AUER5xF8Kqr0YVFuQ6teaJR2u/WE6OyssEh011A9dPPYVnqw33PnfWKhmql0B4P5V9+lfWuBsaqlTgnPo312/mYO+5I8NzRmN260X63nVHRaNLXaLud9b8nVoCo9euxLvwWXViYWDmag7pUxOMUn3kKtjmzUbU/18SHcwdVz7xA8fBT6v1NNVatpPjkYRirV6KiUbTNDlpTPf5ZIkccnf3400hVV+EaNxbnKy+iggEiBw4mcM3fiPfZLdehyXtbHpBrkFtNmVtIkqKNajewH5Zff0l6TDscbJi7ELNzlyxH1XSONyfj+euVGP6aBse000n51Jn5028+Hqf97rtglDVc2mq6C6i5/yGKLh0tfzxzTN7Ack+uQe5JkkI0h+3zTykaPQqjOvnvb/jIoxNtwWuSvGfbbATPOR//XfdlOsw6tmlfUHz2GRCPo8JhtMUCdjv+6/+O88WJWH9a1jBOIHrIYVT+962sxbk1jjcn4xlzedJuZma7dhhr1rCuvH7NKrTGNmMa1sULMTt0JHzMcZCivbpID3lvyz25BrnVlLmF1KRoo1SKCQSAtlq3eDyfhI8dhtm5c4O2ZNrlInzkMfmToACs8+ZCuGFrLEh0tXA+/yxMn479w/cTha3aILV+Pa4H76V42FEUnXU69g/fb7iPWQghRF4yqipJ2WqK2qKNKZbcq2gUx0cfZCiyJMJhis4diQoE6rYGqHgcFQxScM8dBC++DJ2s5oTLhf/v/8henI3gfP7ZlO3WiURgyhTsH72PbcY02LjFQymiBw0meMkVhE89Y5tPUNhmTqdw9DmUDD0C9+23YPz+W65DEkJsgdSkaKOig/bB/vGHyYsnKYP4jjtlP6jmsNupeO8TPNf9FceH7yXuggChcy/A//fbchvbZpS/GlTqvKBt7hw49lgKUahImPBRx1L96DhINknaBlmW/JCopB4O121Dsk2fRvTQw6h6+oWcbwMRQgixZdH+A1NvkXA4iQ7cF8vyn1O+Xmexq4n94w9Bp0iCx2JYli2j6qmJeP5+PcaaNaBN4j17UX3vf/Ku3pOqqkp9LByG006j0OkCNFisVI99stVv62iKgptvwPXiRAgGUVpjXTAf97PjqXz5daIHHJTr8IQQSchKijYqcO0NSVs1mW43gSvHtKr2Z7q0HdUTnmP9D8spnz6XMt8v+G+7s8WFKNMttmd/VCSc9JgGVDwG1dUY1VWocBjHR+9T+H+XZjfIHCq66FxUVVW9OilGwI9t6mc43khed0QIIUT+MHfYkcjhRyRaTW9CA9phJ3DN31LW29BOJ6Hh2etqYqxdk7LTlIrFMP74nchRx7Bh7kI2zF1A2TffU/7lbGL77Z+1GBsrcthfUid4olGIRjGqqzCqqzEqyikafQ6WRQuzG2SOWGfPwvXixMSKmdobcyoSQQUCFJ131p8rS4QQeUWSFG1UbK/+VD39PGaHDpgeDxQVoZ0ughdfTnDMtbkOr3k8HsxuO+RtgkW3b09o+MgGLctSrYxVoRCO96dgrF6V+eByzLLsRyy/rEi6sscIBHBNeDIHUQkhhGiqqscnEB56fKIldlERFBQQ77kzFW99gO7UieqHxqJdrnrvfdrhIL5910Sh6yyJ9e1Xt/pyc6bTRWzAwMQXSmF27oLebrusxdZUodEXJ1qPb/a4hqQdSgiHcT/8QOYDywOuiRMgGEx+MBbFNu2L7AYkhGgU2e7RhkUOP4qyRT9iXTCfUqdB2Y67oD2FuQ4rf8XjWL7/DmXGifXpC3Z7k4eo+ff9aLsd1wsT0TY7KhaFuJl6hYXDgXXxQiKtoIhpS6iyMrTVhiL5RMIoK8tyREIIIZrF5aL6iQnU/PPfWH0/UNJrR8o77VRXiyI65HAq3nwP9913Ypv3FdrlJnTmSIJX/jWrc5DYPvtidtsBtezHRKvUTVmthEacnbVYVFkZluU/YXbukrjZ0kRmp85UvP0hRZecj+XXXxLvp+EQaJ1YSbH5+UwT27w56Qg97xlrViff2gygNcYGmV8IkY8kSdHWWSzE+g+EjoVoqXabkn3K2xRe91cIBhITLcPAf8vthM65oGkDWa3477yXwA03Y/EtQZeW4rnhWuxffJ78+XETs7Rdy7+BPBfv3RsViSQ9pg2DaP8BWY5ICCFES+iOHYl27AgdC2Gz+UVs7wFUTXojR5HVUorK19+m+IyTsKxYjkaBocDppPLF19Dt2mc+hpoaCv96BY4PpqDtDlQkQqzfHlQ99WyTkxXxvrtTPm0Olp+XoTZsQDsclA49MmmSAsAsKU3Hd9Ay0Sj2jz5I/PxtNuK9vcT77IbZqXP6TrHv/tjmzakrjropFYsR67dn2s4lhEgfSVIIsRW26V9SdNmFqM2WC3puvQld4ElUxW4iXVhEbOA+AATPHY117hyMgL/h84qKEkmkbZwubUfolNNwvvE6KrTZagqHg8BVV+cmMCGEENsss1Nnyj+fiXX+11iW+jC360R08KFgzc70uHjUcGxzv0oUjK79EG2d/zUlxx7Ohtnzwe1u8pjxnr2gZ+3/79EDy5IfGqwk0G43oQsuanH8LWFZvIiS006AYAC1aWcSm43I4UdSPfaptKysCZ03GteTYxskKbTdTrT/QOK9vS0+hxAi/aQmhRBbUXDn7Q0SFECiTdkdtyWWU7ZA5JihRA4/EtP9Z/svbbdjFhRQNeG5lO3atjU19zxI+JihiX3MnkLMwkLMoiKqnnyW+O79ch2eEEKI1kBrrN9+g/39KVh+Xrb15ytFrP9AwsNHEh1yeNYSFJbFi7B9PbfBh2cVj6Oqq3C81fKVJlXjnkEXFtYrlG66C4gO3IfQmWe1ePxmC4UoOWUYqmw9RiCAgj//RaPYP/2YorOHp+VUZqfOVL72JvHtOmF6PJiFhWink+i++1P13MtpOYcQIv1kJYUQW2Fd8G3KY8a6daiKcnRLtmQYBtVPPYv9ow8ofnki0ZWriR50MMHRlzRrb2qr5XBQ/eQz+P/4Hes389CeQqIHHtys2h9CCCHaHotvCUWjhidahlosqGiE6N4DqHr2xexs39iSeBzbrBmoDWXEd++H7atZKW9yGH4/9s8/JdzCREK8z25smPE1HSY9R/SdKeiiYkJnn0P4uBOyloxJxvHeOxCJJC/qSaL7hu2beVi+W0y87+4tPl9s0L5sWOjDNnsmav064rvtTrzXLi0eVwiROZKkEGIrtNOJqkm+pxOt0Y6GrVybzDCIHH0snH0GFW28NojZtRuRrt1yHYYQQohWRFVXUXL80aiK8nrbG2zz5lB8+klUfPxFzlYm2mbPTLS7DIcBjYrGiHXvgTaMpB/UtWGgS0rScm7dqRP8619UXHV9WsZLB8uPS1H+mi0+R+vEtUtHkgIAwyB6wEHpGUsIkXGy3UOIrQifchraZmvwuDYMIgcNbtaeUSGEEEKkj+O1V1HhUIP6CyoaxbpsKdav5+YkLuOP3ykefgpG2XqMmmqMmhpUOIR1+U9Jt5IC4HASOv3M7AaaRWbXblufO1kt6KKi7AQkhMg7kqQQYiv8f7sZs+N2aIej7jFts6OLiqm5p230GRdCCCHymW32jPoFGDcVj2NdMD+7AdVyPv0UxJK0AY1EwGpFOxzoTVZ4mG43oZNOqSuuvS0Kn3BSopvKFqh4nPARR2cpIiFEvpEkhRBboTt0oHzqTAJjriW2cy/iO3UneOHFlE/7CrNHz1yHJ4QQQrR55nad0BZL0mPaZkPnqOWmfc7s1C22nU78Y64j8pcjiHfbgeigfah+dBw1/3ksy1Fmly4somriS2i3u8E100qhXS6qH3wUPJ4cRSiEyDWpSSFEI+iSUgLX/I3ANX/LdShCCJF2WmtCte1/XS7ZwiZan9CIUbheeA7iSbpxxU3CRx2blvNYF8zH+dwzGH/8QWzQPgTPPi9R9yGF+HadsELydQMaYvvtT/Ca/KkXkS3RQ4dQNm8xzldfxP7Zpxi//QJaE9urP8ErxxDbc+9chyiESIN4PE51dRUlTUwUS5JCCAHxeKJKVQ6rfQshsicej7No0QLKy8upqEj8C4VCDBw4iEGD9st1eEI0Wbzv7gQuvQL3uLEQCqK0RlutYLNRNfbJtNyVd9/3b9yPPQThMMo0sc+ajmvsw1ROepPYPvsmfU3ovNHYP/s4+VYUp5Pofge0OK5UVFkZzpefB993uDt1JXT2uZjde2TsfA1oDZFIoktXkqKlukMHgleMIXjFmIyGYfl5Ga5HHsQ+fRra4yF4zvmERoyCTbbxCiHSY82aNSxf/lPd3KKyshLTNLnggotxOhv/OyefSIRowyy+JRTcciP2aVPr7mDU3H4XsX3lQ4oQrd369evYsGEDFRXldcmILl22Z/DgQzEMg3nz5mCz2SgpKWXnnXtRUlJKly7b5zpssY2wffYxBfffA0uXUNquPcELLyV03uiMJsMDN95C9NAhuMY/gfHbb8T67UHwkiuI9/a2eGzr/K9xP/ZQvWKXKhRCAcWjhlO2+Mek31v0oMGEzxiBc9LLEKxNntjtaJuNymdfQlVUYGwoI96YYpJNiXf2LIrPPCVxEyIUxG2z4R7/BDV33kvo7HPTdp6ktMY54UncDz+AsX4d2ukidNYo/DfeCgUFmT33ZqxzvqL49BMTRVXjcQAKbrsZ52uvUvHme5KoEKKJwuEwa9euqTe3qKgoZ9iwkygtLWXdurUsWDCf4uISSkvb0aPHzpSUlDa5uZLSKXo0Z1F3YHlZWQ2mmfNY2qyOHQtZ18ZbX+aDbF4Hy7IfKTnyEJTfX68auna5qHxlcptt1SW/C7kn16BxtNYEAn4qKirqJgpWq5X9au/MvvLKC1RUVGAYBkVFRZSUlLLDDjux++79AIhEItjt9qRjG4aifXsPQA9gRVa+ofTqjswtcsY54Uk8/7q13gd60+Umuv8BVL38OhitrySaZ8xlOF99GWWaDY6ZnkKqnn6e6GF/Sf5irbHNmIbz2QkYa9cQ3Wc/IsedQMFdt2ObNQNtt6PicYKjzsN/678gSUexJgmHab97L4zKyoahOJ1s+GJ2RmtqFdx0Hc6XXsAI/rl6RDscxPr0peK9T7K3alNr2g3aA8uvvzQ4ZLrc+G+/g9C5o7MTC/Lelg/kGjROLBajqqqyXhJi9933oFOnzqxY8TPvvz8FAIfDQUlJKSUlpfTvP4CSklJisRhKKSxJagQ1ZW4hKymEaKMK7vonKhBo2K4tGMRz03WUT52Vo8iEEJuKx+NUVVVRUVFOIOCnb99EkuH999/ll19W1D3PZrPRtWu3uq8PO+xw7HYHRUVFWJN8KEiVoBCiJVRVJZ5/3oIKheo9bgQD2L6ahW3qp0SHHJGj6JrP8vvvSRMUAGgTY+2a1C9WiuhBg4keNDjxtd9PuwMGYKxdg4rH6wprOp9/FmPdOqrHPd2iWO0ff5hYQZFMPI7zhYkEbv1ni86RirHyD1wvTESFw/UeV+Ewlh992D/+kMgxQzNy7s1ZlvyAWr8+6TEjGMA58ZmsJimEyDehUKguCVFa2p5OnTqxYUMZr732CpsuZCgsLKJnz14AdO68Pccfn1g14XK5UZstkUg232gOSVII0UbZP/0o5YTL8uNSVEV5zqqhC9EWhcNhKirK2W67TiilWLRoAd99t6huPyeAxWKhT5++GIZB7967ssMOO1FamriLUVBQUG+y0Llzl1x9K6INs3/6MdpqTVoo0vD7cb76cqtMUkQHDML21awGH74BlGkS2233Ro/lfH0SqrKibvvBRkYwiGPK2/h//QVzx52aHauxeiUq2rDtKYCKRrH81nBlQbrYP/8UbbGkvP6OtyZnLUmhaqohRceXRDw1WYlDiFzSWlNdXYXWmuLiEqLRKFOmvE1FRQXBTVY77bVXfzp16kRhYSEDBgysWyFRUlKCzfbnTQ2n01nvhkimSJJCbLtqanC9+BzOV1+CSITw0ccSvPjyLVbhFkKITNp4Z0IpxerVq1i61Fe7r3MDgdrCeqNGnUdBgQer1VpvP2dJSSmlpaUYtUvle/XaJWffhxAphcOwhS02KuDPYjDpEzr3AtxPPg7UT1JoQJuagjtvJzTiLCLHDtvqdgb7h+9hJCukCWirFdusGYRbkKSI9941kShKklAxnS5i/fZs9titSaxPX1QsebJGW61EDj4kyxEJkTmmadbND+bP/5r169dRUVFBRUU5sViMXXbpzeGHH4XVasVms9G9ew9KSkooLS2ltLQdHk8hADabPS8KaEuSQmyTVHUVJUcdhuWP3+v2xFqeWoHrhYlUfPgZ8dolS21Z+PAjcUx5J+lqilhvr6yiEKKFgsEgK1f+UZeESCyprGDYsJPo1KkTVVVVLFu2lJKSUnbcsXttEqKkbhtGnz596dOnb46/CyGaJnrAQQ1WCGxkFhQQOea4LEeUHmaX7al85XWKRpyK8icSLWrjv3AIx2cfY5s9k9gz46l87c1ER4sUtHsLxSOVgXa5WhRr9KDB6A4d0cFgw/d4i5HobAFYvv8O58vPJ+pk7H8g4VPPQBcWtejckSGH49nC9Q+feGqLxm8Sj4fg6EtwTXgSFayfFNJ2B4EMdxURIlPWrFnD+vVr65IQ5eXlFBYWcsIJJwPw008/EolEKCkppWvXbpSWltKhQ0cgcZNk6NDjcxl+o0iSQmSV5acfcbz4PJaVfxAdMIjw8BHoouK0n8f10ANYfvu13l0EFYlALIbn6quofPO9tJ+ztQncdCv2zz+FJIUz/Xfdl8PIhGg9gsFg3X7OjQWm+vXbkx122JENG8r46KP3gcR+ztLSUrp06VqXhOjVaxd22aV3g/2cQrRm5o47ER52AvYpb2NsUjhTW63oklJCJ2XgQ2o0iuO9d7B99AE4nYRPPSPR2jPNv1vRPfcGUyfdygBgBPxY53+N65nxBC++DOvXc3G+Pgn8fqJDDic89Hiw2wkPH4H9048w/A1XlahYlOiQw1sWqGFQMfkdSk4Zhlq/HiMWxbTZwLBQ9eIkdIcOuO+5E/fYRyAaQcXjOD76gIK776Di7Q+Je3dt9qnNLtsTHHUezpeer7daxHQ4iPfelcgRR7Xse2si/9//AYBrwji01YaKxzA7bkfV4+Mxe+6c1ViEaCzTNKmqqqydWyQSEZFIhKOOOgaAefPm8OuvK7BabZSWltC5c2e22+7PleInn3x63aqK1kq6ewighdVuTRPni8/heuwhLKtWYnbuQuCKMYkWV5v8gjjHPYbnrn9CLI6KRTHdbrDaqPzfu2lfeth+t54YKYolaZudsu+XoYtL0nrOdMh21WHLUh8F/7gJ+9TPwDSJDRhEzW13puz33hZI5efcy7drYJomNTXVdUmI9u070K3bDlRWVvDyyy/UPc9qtVJcXMLAgfvQs+fORKMRKisrKS4urrefszWQ7h6iRWIxCu74B86JT2MYBjoSJTL4EKr/M7ZJWy6NX3+h4O47sL8/BaVNIocOwX/jrfU+RKsNZZQcdyTGqpUYfj9aKbTLTXTIX6ga/9wWaxI0lf2dtyj8v8swarb89ynWvQexQftin/J2ok2paWIWeDA7dqRiyifo9u0pGnka9pnT63VA0S43NensOGGa2KZ9QcmqX6gsKCVy5NHgcGCdPYuSM06sd24ArRRm9x5smD2/ZQkerXE+8xTuhx7AWLsG7S4gdNY5+G+8Ja1tVpukpgbrku/RhUWJlrQ5SA7n23tbW5Rv1yASidStsqyoKGfgwH0wDIMvv/yc775bXPc8t9tNu3btOe64E1BKUVFRjsVixePxtKobHU2ZW6Q9SeH1ev8B3Ab08/l8i7fydJCJRF5oyS+tZ8xlON58o37G3O0mfPzJ1DzyOACWxYsoHXp4gzdEgHjnzmz4dklaW5K179459X5Pp4sNs7/B3L5r2s6XLjn742maoHVaJ3OtVb69gbVFuboG0WiUiopylFJ06NAR0zSZPPm1uv2cG+25514ccMDBmKbJwoXfUlrajtLSUjyewlZ/52KjfExSNHF+0R2ZW+ReKETHcCXrtb3JWwiNX1ZQevjBqJqauu0jWim02524299vDwCKzj8L+4cfoKKReq9P+wd+wPHKi3huvDbl/GIjs/aD+ObP01YbkUMOpeqVyRCL4XzuGVzjn8DYUEZs190IXPM3oocclrZ4N9r8b2rhBaNwvPtWg+5ekNiSUfnGu8T2HpCek0ejiRodreiDVKbI/CL3cnENNm0X3rHjdtjtdpYu9fHVVzOpqfmzeKthGIwYMYrCwkJWrVpJZWVlXWFsh8OR1ZgzJWctSL1eb39gP+DXdI4r8pdlyQ84/ze5QfLBCARwvjWZ4KVXEO+zG65nx0MkknQMVVODbcY0omksYBTbqz/2mdOTHtNuN2anzmk71zZhG/lgJcTWaK2JRqN1Wy7mzv2KtWvXUF5eTnV1FQA77dSdY48dhmEYtG/foW4/58bila7a/eKGYbDXXv1z9r20JTK/aKWcTtihI7oZHwoK7rgNVV1dr6aCBB9nIwAAIABJREFU0hr8fjw3XUflOx+iqquwf/RhgwQFgAoGcD3xWFqTFLEBg1K3Ia1/dowkBUJVLIp9+peosjJ0+/aELriI0AUXpS2+xrL89mvSBAUAhoGxenX6TmazpW8sIfJYPB5Ha43VaqWsbD0LFsyvW4EZqf0MdMIJJ7P99l1xu9107dptkw4apRQXF2OpvVnYpcv2dOmyfS6/nZxLW5LC6/U6gLHACODzdI0r8ptjyjuJLHkykQiOd98i0Gc3LCuWpyykhdYYq1amNS7/DbdgS7KU0XS58V97g6wYEKKN+OOP31m7dm294pWFhUWcdtpwANauXUMwGKBz587sumsfSkvb0a5d+7rXD2np3nDRYjK/aJscH7yXNCGgANvXcxP1lNavR9usqEjDLhYAxv+z995hcpRnuv5d1TlX9eScg3IGgSIiCJDBmCCyAeO1d9f22t7jDd5w9vis/VuH9e5Zn3Ps493F9ppksMFgEwyYIEwGAQKMNSCU00iaTtPT3dOpfn/0VE33BJA0PdMTvvu6dCHN1FR/xdTUvP1+7/M8x48XdU2Zzi6SZ63JyTTGSM6AnK/Th9UYmsWKfPwYmbKycY+ZbNKLFmN+e8eYdZmUSpHp6CzBqgSCmcPg4CB79uwuqC0ikQibNp1HR0cX6XSaQ4cOoigqXV3z8PkU/H6/YV5ZX99AfX1Dia9ielPMSYr/CdzR09Ozp6urq4inFUxrUkkYr/mQzRoNjNTipbl88bGmKTQtpw8sIunVZxH5wW14/tsXcnFokgzZDLEv/0VJdi0EAsHkoOs59d2KUChIPB7nssuuAODdd99h1673cTqdKIpKe3snZXlvDmaCw7VA1BdzkvFqiyGkbIZsdc2HTjZkJsEYMfKjO/B88U+x/ebhnEwylQJZRrM7QILot/4F+09/jPWVl8ZedzpFtq60ctP4Zz+XM/Qc6UlhtpBaupyMiDcWzHE0TSMajeYlc+XqjPb2DhYsWEQymeTpp3+LyWQaakCU09bWgar6AaiqqubGG28p8VXMbIriSdHV1XUW8A3g3J6eHq2rq2sv8LFT8aSY8CIEpeH552HzZhjDoRqXCx57DNasgX37YP58GKnjNJtzH3/zzcnRK2YysH17TmqyYgVMMNZLIBBMPXqxEAgEjD/r16/HYrGwbds2XnvtNSAnv1CU3G7Fli1bMJvNRKNRzGYzdru9xFcxYympJ8UE6otmRG0xsznvPHjyybE/t3AhvP127u9f+ALcdtuoN9y4XHDHHXDZZZOzvt5e2LkzNzXR25urL845J/ffRx+FK68cXfPY7XDttfCjH03Omk6F+++HG2/MrT+Vyv23sxMefxzKy0u9OoFgSkin0wSDQaO28Hq9LFiwgEwmw/e+9z2yQ01Qu92O3+9n0aJFLFy4EE3TCAaDKIoya7yoppipMc7s6ur6a+DPAH2bvB7oBW7p6el5/CO+vBlhblVyTttIRtPwfWIL5tdfQ04kjA9nbXbSy1fkoj6Hmg+Wp57Ae+snQZKQkkk0i4VsTR3h+39NtrrmtNYtHTuG/d67MO3ZTbp7PoNbr5mWqR0nizBVKj3ie1A6MpkM4XAYSRrEbldwOBy8/34P27Y9TSpPVma1Wrniiq0oisqJE8eJRCKj9JyCiTFdjDMnUF80I2qLacHpPlPNO95AufTC0QkUdgfhn95NauOm3AeSSbyfvgnrM7mGhibLSJkMA1/+C+J//pent2hNw/L877A+8hBIEsktl5A6a80pbaY4/s+/4frW19FMppysQpZJnnkWkf+6e8o3TMb9HkSj2B57BCkYIL1kGemVZ3zkNZp3vIH9P3+Iae8e0gsXk/j0Z8i0icmLk0HUF6VDjwv3+ew4nblphwceuI+jR4+gvxeWJImOjk7OPfcCAN5/vweXy42qqtjtjhmVojFdKWm6B8DpTFKIQqK0TOjBGY/j/trfYb/7ztzooySRuOY6ov/jG6N/Ecdi2B57BPn4MdILFpE6e+1pT1BYH/413j+5FTSQBhM5N21ZJnzXfaRXn3V611JixC+w0iO+B5NPIpFAlmWsViuBQB8vv/yioefMZrO4XDY2bDifpqYWent7ee+9nUaChqIoOJ0uUSxMMtOlSTGSU52kELVF6ZnIM9X8ysu4v/rfMO/8A0gSmYYmot/4FqkxvGJMPTux/O4ZsNkZ3HwxWmXl6S04kcB3zeWY33wDKTYAQ5Gm6VVnEL7z52A9+Thh6fhxbL95GCkeI3n2OjILF53emiZIsX6vOb7/PVzf+gYMDiJls2hmC1jMRL7/HySFdO4jEfXF5JLNZonFYrjdbgDeeGM7+/btJRgMkkjkmp2NjbVs2ZKTg27f/irZbNYwxvb5FCzC6HVSEU0KwSlTlAfn4CByMEBW9cMkR+VIvb2UnbF4zEjTrMdL3zvvz0hph/gFVnrE96C4DA4O0tPzhwLfiFgsxvr1G1mwYBGBQIAnnvgNiqIahUJbWz3ZrFUUCyVENCkExaIYz1QpGIBMFm0KZAjOr/09ztt+iJQ3HQq5CY7Y5/6M2F/97aSvodgU43tg2r0LdePZo/6/QM4stO/3u9Dcngm9xmxH1BfF5ciRwxw8uJ9gMEQoFCQcDiHLMp/61GeQJInnn/8dx48fK0jn6uhoJJkU8oxSUbIIUp2enp7myTivYJpjs522bONUsd9zJ4xXeGaz2B59iMHLr5qStQgEcxlN0wgE+owGRM5kKkRraxsrVqwC4Pnnf4fdbkdRVBobm1EU1YjW8vv9XH31dQXnFIWcYDxEfTE30YbM6Cb/hTQc/3XbmG/EpUQcx20/nJFNimJgu/sOSI9tZqrJMtaHf83giGe5QDAREokEfX0nCjY5gsEgW7dei81m48CB/bz++mt4vV4URaW+vgG/34+maUiSxJo160ad0+cT9cVMYVKaFALBZGPasxtpcHQRATnph3zwwBSvSCCY3cTjsYIEDbfbw+LFSwH45S9/QSqVQpIkPJ5cseBy5cYtbTYbN998q9BzCgSC6U8igRQbPaGpI4VCOUPuOeh9Ix89ipQeO3JeSiaR+/qmeEWC2UAmkyESiRQkaKxYsRKfT+GDD97n2WefAcBisaAoKrW1taTTKWw2G0uXLmf58pWYzeLt7GxEfFcFM5LMvPlkHQ7kMeQemt0uTJwEgtMgm83S358rFlKpNO1DMXT33/9zenuPGseZzWba2tqBnNHUBRdchNPpHFfP6XA4p+YCBAKBYCLY7Wg+L1IwOOans5WVc6ZBIQX6cH3z69h+cS9SIk62ppaszY48xgaRZrWSXrS4BKsUzBSSyaSx0VFVVYWiqBw6dJCHHnrQSNAAcLlcdHfPw+dTaGxs5pJLLhva+BjtRWU9BX8YwcxDNCkEM5LE1mtx/tM/jvq4BmB3kLzgwilfk0AwU0ilkvT39+P3lwE586hdu94nHA6RyeTGed1ut9Gk6Ozspq2tfcg3wo/H4ykoFhobm6b+IgQCgaDYSBKxP/kCzn/9zqhNEM3hJP65L5ZoYVOLFAmjnr8B+egRpKFkJdOB/Wjk6qz8t4qayUS2ppbU2vWlWKpgGqFpGgMDA0gSuFxuotEoTz31BKFQkIGBAeO4NWvWGUaVS5YsQ1X9Q54RCrY8TzuPx4PHI3xO5iqiSSGYkWiKSuSuX+C9YStkNaREHM3hALud0H2/BmG4J5jj5EdqHTp0kD17dhujlNFoP7Is8+lP/7ER2en1emlsbCowmNJZWCJHeoFAIJhq4l/4Muadf8D2yK8hk829I5dlEpdeRvyznyv18qYE+4/+A+n4MaNBoSOR85/I2u0gy0iZLOn2DiJ33nvaSW2CmYfu+ZDNZnnjje0FnhGpVIolS5Zx9tlrsdlspNNp6usbC2oLr9cL5DZDVq8+u8RXI5iuiCaFYMaSOmsNfW+/j+2RXyMfOkimrYPk5otEg0Iw54jFBujt7S0oFEKhIFu3Xofb7ebYsV527nzX0HOObELoBpcCgUAw5zGZ6P9/txF7rwfrbx8HSSJ5/mYy7XNHRmr/xT3IY5iHAmhOJ9H/+U3wuEm3dZQsVlUwNfT29hIM5syxc8bYQaqqqjn33AuQZZm33tqB2WxGVVW6u+ejKCrV1dVAzkficmFiLzhNRJNCMLNxOhm88upSr0IgmHQGBwcJhUJ55lIBVq48g/LyCg4ePMiTTz4O5PScuZitLuNrFy9eytKly4VxpUAgEJwkmc4u4p1dH33gbCQzdooHAJJEprub9Mozpm49gklD0zT6+/uNBkQoFMRkMrN2SL7z7LNPc+LEccxmMz6fQnl5JdV5SX433nizMK4UTArirhIIBIJpgqZpRKNRo1Corq6hoqKSI0cO88AD9xnHybKMz6cwODgIQENDI5dfvhVVVcc0kjLNEaM3gUAgEEycwY99HNMP/jdSMjnm59OLlkzxigQTJZVKEQ6HDH+IJUuWAfDYY4+wZ89u4zi73V7QhNi4cRNWqxWPx4ssy6POKxoUgslC3FkCwWwkGkUOh8hWVIJwP552pNNpIpEwJpMJn08hHo/z8MO/MvScOqtXn01FRSWq6mf16rML9Jz5jQeHw4HD4SjFpQhmAbrZWb5cyOPxcP75G0q9NIFAUALin/lTHLf/BEJBpLzkhazDSewLf44UjaLlGRwKpgeappFIxAkGc5scsizz9ts72LHjTaLRfsOrSpZlFixYhNlsprt7Ho2NTYYx9shaoqKishSXIpglpFIpIpFwnmfJIJdeevFJfa1oUggEswjpxAk8f/llrI8/CiYTmmwi/kd/TOwv/wZEt3vKSafTmM1mNE3j5ZdfJBDoIxQKEolE0DSNBQsWsn79OdhsNhwOJzU1tSiKMlQsqEZ0p91uZ9myFSW+GsFMJ5PJEA6HCyRD+WZnOlarlY6OzhKuVCAQlBKtooLg48/g/upXsD7zVO5jQykLru9+E9c//xPpzi6i3/lfpIWn0ZSjR3bKskxv71Hefff3xnM9MeQlct11N+LzKTgcDqqrq1GUeUZt4fX6jAmI5ubWkl2HYPYQj8eNuiL339zUTn9/pMDIvba29qTPKd61CARTjaZh2vU+pFJkOruK1zxIJFAuPhfToYOGI7cEOH74f5EPHyL6f35YnNcRjMmhQwc5ceJ43m50iMrKSi6++BIkSWLv3j3Iskx5eSUdHZ0oikp5eW6HQpZltmy5pMRXIJgtJBKJvEbEsJFqJBIpyKN3uz0FZmc593UFp9OFyTR6rFcgEExvpEgY0769ZCsqyeaN7J8O2cYmInf+HOJxrL9+EO9X/gwpz0zT8s7bKFdcQvDh35JZsHCiSxeMQzwe48CBAwXP83A4xJYtl1JXV080GmX//r0oimpEhSuKitOZ2+Rob++kvV00nQUTJ5vN0t8fKahz9b8nEsORzWazGUVRqayspLOzy0h28fkUbLaTn+4WTQrBnMfy1G9xfu9fMO3eRba+kdjnvkjy4o9NSpyW5ekn8fz555GDQTRJBouZgb/7GolP3jLhc9t+9UvkMSLD5Hgc+4O/JPZXf0u2oXHCrzNXyddz6oWCpsEFF1wIwKuvvsyRI4ex2x2oqkpzc0uBrvPqq68TxpWCoqGbnekNiPz7MhaLGcfpkiK/v5y2to6CZoTFIqRgAsFkIYWCOP79B9h//jNIp0luvojY579Etr6h+C+WSOD+6lew33cvmsWClEySWraC/u//x8Rfz27H/e1vFDQoDOJxXN/8OpHbfzax15jDaJpGLDZAKBQqaCovWLCIlpZWIpEITz75OLIs4/V6URSVpqZmnE4XAK2tbbS1tZf4KgSziVQqOcKoPWQ0x9LptHGcw+FEURRaW1sNuZCiqHg8nqLUu6JJIZjTOP7tu7j+5TtI8VxRbzp6FM/n/ojEjTcz8I/fLOprmbe/iu/m65DiuW6j/uPr/vu/RrNaGbzm+gmd3/boQ8gDA2N+TjOZsP5uG4nrbpzQa8x2csVCjEOHDg6NqfUbGd7btj3F+++/B+RG1jweL+XlFcbXnnPOuVittnG9IUSDQnA6jNRz5kYpQ4RCIdLp4Yak3W4fKl5bhiRDCqrqH9fsTCAQTB5SoA/1vPW5jYMhg2P7T3+C7Rf3EHr0KTJFllN5P3sL1qefREokjGaC5dWXUS7cROClN6DCc9rnlo4fR+49OvbnNA3r75457XNPOpqG+e0dyPv2km1uKanhZyaTIRAIsGdPbirC7/fT1NTCwMAAt9/+Y+M4i8WCqvqNqbeysnKuvvp6fD7fmCbYorYQnA6aphGPx4aiZQs3O6LRfuM4SZLw+XwoikpDQ6NRWyiKit1un9Q1iiaFYM4iHzmM65+/aRQQxsdjMRz/9WMS199Epnte0V7P9c2vQzw+6uNSPI7rG/+Dwa3XTuj8mu1DHhaShGaxTOj8s4lsNkskktPm19c3Yjabefvtt3jttZcxmTQGBnL3hNlsYdmyFdhsNubNW0BzcyuqmhtZG+lo7fMppbgUwSwg3+xs5M7FSD2nx5PbSaurqzPGelVVxW53iGJVIJgmOL/7LeTeXqTUcDqGlE5Bfxr3f/si4V89WrTXMu3eZTQo8pEyGaRoFPt998BXvnT6L2AxQ55MbCTaNPW7kvftxXfDVuQDB8AkQyZDtqmZ8B33TupUaS4uPAhAVVU1mqZx7713EwoFcTgsRn2xaNESmppacLlcrFu30fCjcrlcBc9ys9mM3++ftPUKZjeZTIZIJDKmBHQw7/2PxWJBUVRqa2sLaot8/5KpZno+WQSCKcD20IMMzzOMIJ3Cdv/Pif3Nfy/a61leeXm8V0MOh5GP9UKV77TPP3jlVqyPPTLmNIWUTpM874LTPvdMJZlMIssyZrOZo0ePsGPHm8bIWmYoB/7KK6+moqISr9dLW1s7zc11SFJuV9rtdhvFQl1dfSkvRTALGF/PGTDMziDXHFMUpUDPqap+vF4fFtFsFAimPfaf31PQoNCRNA3L9leQImE07+n/vs/H8uILaLI8Zn0hxwaw/vaJCTUpNNVPev4CLDveHP05s5nBSz9x2ueeNFIplEsvRO49WpBOIr3Xg3LphQRefWtCfmC5xnLCmJx89dWXOHLkCMFgwJDb1dc3cMkllyFJEnV19bS0tNLSUoemWVGU4bhwSZJYuHDRBC5WINCbY/kSjcBQvRsu8KJyuVwoikp7eyeq6jf8IkY2x6YDokkhmLNIAwOQTo39uXQaKRIp6utpdpshKxlFJos2wQjJ5KbzSS9fifm1V5DzJjayDiexr/w1mjq7O/HxeIxdu3YVaPSj0SgXXbSF5uZW0uk0wWAfiqLS2NhU8HAGaGpqpqmpmYoKD8eP93/EqwkE46PrOYclGsFRzTEY1nPmm50VU88pEAhKw5j+DTqyCSkeL1qTQnM6YRxJl8ZwKsdEiH77X1E+sQXicaShyS7NbEbz+Yj9xVcnfP5iY/3Nw0j9kYIGBQxNl4RDWB//Tc577CQ5dOggR44cLph083jcXHPNDQAEAkEymQyNjc1D4/C5xrLO2rXrAUR9IZgQelz4cILGcL07kLdBKcsyPp8PVfXT0tJWMBmhN8dmAqJJIZizJFevwWGzI8VGTx5kXW5S6zcW9fUSV16N4yc/GrW7okkSqWXL0SYqF5Blwnffh+Pfv4/jtn9HDvSRbm0n9pW/JjkLkiOy2WxBl1h/QC9YsIju7nnE4wmee24bVqt1aBy+3ngwQ25XQy8oBIKJMp7Z2YfpOXNZ9FOn5xQIBKUhtfIMrM9tG/NzWUUhW1E5/IFoFNsTv0EKh0mtWEVm0eJTeq3keRcgpTNjfk5zukhccz0TfdKkl60g+OhTuL71dSzbnoahCYrYV/6abM3JRwpOFZbXtyNHo2N+To5GMe94vaBJkUgkRr3xi0ajXHXVNUiSRE/PTnp6/oDH40VVVWpq6gokGJs3XzTp1ySYO6TT6QIvqvz7Mj8u3GazoSgq9fWNxqaboqh4vd4x/UtmGqJJIZizpM9cTaarG+n3byMlhxsHmsVCtrqa5FBqQ7GI/flfYXvkIeQTxw0fDM1sRnM4iP7zvxXnRaxW4p//EvHPT0B/WmJ0PWcwGCAYDFJWVk5nZxepVIp77rnTOM7tdqMoqjH+rigKn/zkLTid029kTTBzmZie04/X6y2ZnlMgEJSGga/+HZYrXzGMsnU0h4OBv/0HY/LB9sB9eL74ObQhzwQJSC1dTuSOe9A83pN6Lc3jpf+fvoPnb/4iN+kw9PGs00ny3PNJrdtQlGvKzJtP5Cd3FeVck022ogLNZivwHMsCEUmiz+7gcCpF77anWL16DTabjbfeepPt218Fch4QPl/OHyKdTmGxWDnrrLNZt26DkNsJispYceHBYIBIZNiLCgrjwvVmhKqqOBzOWV3vispJMHeRJMK/eBDPF/8U6xOPoVltSMlBkmetpf/7/zEhveJYaGVlBJ9+HscPv5+LJEulhiPJGpuK+lrTnfz4REmSaBgysbr77tsJhULGcSaTifnzF9LZ2YXNZuP88y80IrhGjqzJsozL5Z7S6xDMHvL1nPqO2nh6TlX109HRlRfnOT31nAKBoDSkV51J+Md34PnyF5DCYZAlMJkY+LuvGUleprffwvPFP0XKaywAWF5/Dc+ffJrIHfee9OsNXv9Jsq1tOP/1O5j+8HuyFZXEP/OnOUPuOfZcSqWS9G3YRPbb/0SjlMStafSYzTxqt5ORJDSTmbjThX3PHhYtWoLNZqO9vZOqqmpUVcXt9oxKRHI4nCW6GsFMJ7/eLZzWCRHPk4DrzbHy8ko6OjrzJKBzNy5cNCkEcxrN4yXyozuQTpzAdHA/mZo6tKqqyXs9RSX2V39L7K/+dtJeYzqRTqeJxQbwDmlvX3zxeQ4ePFAQn1hZWWU0KTo6ujCZzKiqMjSy5isoFtrbO6b+IgSzBk3TiEajY05FjNZzKjNezykQCEpHatP5BN78A6aenZBK5dLC8nbinf/332BEuhiANDiIddvTyIcPka2tO/nXO2sN4bPWFGXt0x09PlGWTdjtdgKBAC+88LsCuZ35wou44rFH6Uwk8GezLM1k8JtM2P78L3Hc9KmCuHC/3y8SNAQTIpVKEQ6HRtQWuX+n02njOLvdgaqqNDe3GP4lOS8qERc+EtGkEAgArbycdHl5qZcx49m/fx8HD+4viE90Op188pOfAnIPcafTSW1tnRG3lV8YrFx5RqmWLphFjNRzDk9GhD5Sz6mquWJhNug5BQJBiZGkcaPMzW/vGGXsqKPZbJh2vX9KTYrZTDKZ5Pe/f3uU3G7NmnUsXrwUs9lEIhGnpqYGRZmfM8a++jrUP/kzErf9O8r7PZzZ1U38j/6EzIKFpb4cwQxlvLjwYDBANNo/Tlx4vRFdr6r+guaY4MMRTQqBYA5gffTh3BjoB7vIVlYS/+PPk7jhJjjFN2Kx2ADHjx8riE8Mh0PccMPNmEwm9u/fxx/+8HsURS2IT9Q0DUmSWF9kM1LB3CYej485FTGWntPv91NTM9wcmwt6ToFAMIy8+wMcP/5PTO/1kOnuJn7zp8m2tJZsPdm6enj/vTE/J6VSZKuqp3hFp44U6MP5vX/B/vN7IJkktW4DA3/xVTLz5p/SeTRN49ixY6OMsZubW1i9+mwkSeLll1/E6XTmxSeqRjS41+vjyiuvGX1ifxnR732/GJcqmEPoceE5b7RCw/aRceGqqlBdXY2izDNqC59PEV5URUD8HxQIZjmOf/0Ozv/1XeQh7ZvcH8H9D3+D9dmnifznT0fpVfX4RP2BHAgEWbt2HS6Xm56eHl566fnceYfiE5ubW0in05hMJs48czVnn71WjKwJikY2myUa7R/lch0MBkkkhk3phJ5TIBCMh+2+e/F8+QuQSSOlUmjPbcPxk9uIfO8HJD9+eUnWFP+jP8byyktIscJock2SyDS1kOnqLsm6ThYp0Ie6aS3y8eNGapn1kV9jeeoJwj9/kPSqMwuO1+MT85vKTqeTFStWIUkSjz760JCEQzYSkfR0LovFwqc+9RkhtxMUlVQqWbDpNl5cuN4cE3HhU4toUggEsxjp2DFc//LtAodrAGIxkk8+Qe/DD3G8uZnGxka8Xh+7d3/AY489Mvz1koTX6yUWi+FyuWlrax/qGKtjjqyJN4OC0yWVShlNiPfeG2Tv3sNGsTCWnrOlpdWI8xzP7EwgEAikY8fwfOnzSIPDO6BSKgWpFN4v/DF96zag+cumfF3J8zYTv/ZGHHfdDoMJpGwWzelEszuI/Pj2KV/PqeL43/8rl1aWF6suZbNkYzGSX/o8e356N6lUiu4hucuDD97PkSOHjWOtVivNzS3Gvy+44EIcDue48YmiQSE4HUbGhWtagr17DxkxszqyLBvG7E1NzQVTESIuvDSIJoVAMIsx/+Zh+sxm7Mmcw3VAkviNw0FAlklIEunb/h/JCy7knHPOxev1UV5ezhlnrDYezl6vr2Bkzev14vWeXCyaQDAS3exspKlUMJjzL9Fxu+2YTLpfRENB/rfQcwoEglPBft/4KRkaErZf3kfi1s9M4YqGkCQG/uk7DF51Nfa7bkc+cYLkho0MXnUNmtsz9es5VX7xM3rTaXRRyktWK+9aLIQliczxY8TvuxdbRaXRpOjunm/INBRFGRUXXiv8NwQTIJPJEA6HR0mGQqEgyeRwI01VPVgsTurq6gumInw+n/CimmaIJoVAMAvIZrPIskwqleL1118zzAIHnn8Ws9XKmlSKs5JJHIBZ0+hOpfBnszhVP9YbbsbtzkV3er0+VqxYVdqLEcx4stkskUjYMJXKN68czJvqyddzdncP6znb2xsIBuMf8goCgUBwcsi9RwqmKAo+l4gjH+ud4hUVkl6+kujylSVdw3jkGwEeOnSQXbveM8bjpayG5HLxhf5+rIBF0yjPZOjMZlEBedN5+JYsNc7VPY6BqEBwKuTiwoMjJKABIpGkEFHdAAAgAElEQVRIQVy42+1GUVQ6O7uN2kJVVZqaqjlxIvohryCYLogmhUAwwzh06CCBQF/BA7qpqZkNGzZhMpl45523cLlcOf3ceRfS9PhvqBlKNHBoGlvjuTd/WZeL6KWXMeiZATs2gmlJMpksuA/1wiESCY+p52xv70BV/cbOhdvtHlPPKQynBAJBsUgvXEzW5UYeGP3GJOt2kx4j7UE+fCg33bBvL5lFi0lsvRZtyB9htjIwEOXIkcMjJt1CbN16DT6fQiDQx+7dH6CqfpqbW6hdtITq3z2DLrJbkUqxYqjWyHq89C1bccrm3AIB5Jpj/f39Y05FxPI8XEwmE16vD7+/jLa2DsOHSlHGjwsXHhIzB1EJCgTTjJHxiaFQELvdwZo16wB45pmniETCWK1WVNVPfX2DMSYpyzK33PJHBdp874P3Y332GcgzGdQsFrJV1QxefMmUXptg5jGW2Zn+Z6SeUzc7a2pqNrwiFEXFZrOV8AoEAsFcZvBjH8f937+KFhtAykv90SQJzekieeGWguNt9/8cz5c+B5qGNDhI9le/xPnNrxP+2S9Jn3HmyNPPGMaLT1y5chVVVdX09vbyxBOPjYhPrEOWc42GBQsWsXDhYuNNnqmmFmXzOch5sc4AmsNB9O+/JhoUgo8knU4TDofG2OwIkU4XxoWrqp+Ghqah2iLXiPB6fcKLahYjmhQCQYlIJBIFkUZLly4H4OGHf8Xhw4eM49xujxGzBbB580U4HI5Rek6dkQ/syG0/xf0Pf4P97jvQZBkplSJ57vn0/8v/AWFEJRhipJ4zF72V+3sqrwi1Wq1G9rfQcwoEgmmP3U7ogUfxXf0JpFAINA0kCa2sjPA99xf8HpQPHsDzpc8h5cUMykPTh77rr6TvnV0wzZuuenyi3liurq6hosLDsWPHuP/+YX8Os9mCoiiGXr+urp6rrspNTVgsllHnHVlbZLq6Cd//azx//gVMH+wC2YTmchH9+68xeO0Nk3uRghlFYVz4cKxnf39hXLjH40VV1YK4cL/fj93uEBMQcxDRpBAIJpH8kbWGhkYkSeK1117hnXfeJh4fHlmz2WwsWbIMgCVLljJ//oJx4xPLyytObRE2G9Fvfpfof/9H5KNH0MrK0HzKhK9NMDPJb47l716Mp+fs6pqXNxUx2uxMIBAIpjuZzi4C29/B8sJzmPbvI9PcQuqsNaMiuO13/hTynoOFJ8lgffw3JC/5+BSs+KPR4xPNZjN+fxmDg4M88MB9o+ITzzhjNYsWdeL3q6xZs27c+ESbzYbNdmr1RXr5SoLPvIh89AgkEmQbGsUExRxlZHMs3xh7rLjwyspKOju7jInL8ZpjgrmLaFIIBEUglUphMpmQZZkDB/azc+e7xgNaj0+8+eZbcTicuN0emptbhuIT9WLBaxQLzc2tk7NIp5Nsa9vknFswrTh1PWf5Ses5BQKBYEYiy6TWrif1IYeY9u5GyksCyEdKJjEdPjg5axsHTdNIp1PGZsULLzw35EkVMOR2XV3dbNp0viEBbWxsKkhE0uMTLRYrixcvHfe1JkK2umZSziuYfqRSSaO+zTfHHhkX7nA4URSF1tZW414UceGCU0E0KQSCUyQajbJ//17j4ZwrFvq54oqtVFRUEovFOHbsmKHn1B/OepHR3T1PuFwLikIqlSrwL8klaOTMzvL1nHa7HUVRaWzUs7+FnlMgEAhGkl6wiOzDDyEnRqcLaVYrmfaOSX39Awf2c+LE8QK5XUVFJZde+gkAjhw5jKZp1NYO1xbl5eVAzhDwggsunNT1CeYG+XHhhR4mQaLRfuM4SZLwer0FceGq6sfnU0RcuGDCiCaFQDACfWQtXzcXCgVZsWIVjY1NBIMBtm172tBzVldXoyjzsNlyuxVdXd10dXWX+CoEswm9WBi5c5Gv55QkCbfbg6qq1NbWGTtpqqoKPadAIBCcBIlrb8T53W+N+rgmSWgeL8mN507o/GPFJ2YyGbZsuRSAHTve4MCB/bhcLlTVT2dnN5WVVcbXX3HF1gm9vkCQTyaTIRKJjCkBHSsuvLa2tmAqwuv1iTQuwaQh7izBzGFwENtvHkbeu4dsYxODF30MhsYYTwddz6mPrVVX19DY2EQoFOKee+40jtPjE3Wqq2u4/vqbRuk5BYKJcCp6TkVRh/ScnUakp9BzCgQCwekh79mN7bFHIJMl+o1v4/67vwY0pMQgmt2G5vYQvu/XJ+W3oGka0Wg0T24XYu3a9UiSxAsvPMfOne/mXlOW8fkU/P4yNE1DkiQ2bNiEzWYTcjtBURk7LjxAOBwu8KLS4+vb2zsLJEPjxYULBJOJaFIIZgTmt97Ed9XHIZVCisfRHA7cf/llwj+7n/SKVeN+naZpxGIDhEIhzGYzVVXVpNNp7r77joKRNVmWWb58JY2NTfh8Ps455zxUNffGzz6iEWKxWMSbQcFpM1LPGQgEDT1nvtnZeHrOfP8SgWCiZLNZotF+o4AtL68oSBMSCGY1mob7q1/BftftudSPrAYmE8kNGxm89BPIx46R6egguel8GLFjnB8X3tjYiMVi5Z133uall54vSESy2WysWLESp9PF/PkLaWlpMbyoRiYieTyeKblsweyjMC48UNCUGBgYMI7Ljwtvbm4dqi38KIoi4sIFRSWZTBqN2nA4yMqVZwInX7+KJoVg+hOP47vyUuRQyPiQNGQY5dv6Cfp27CTjcDA4mMDpdAHwu99t49ixXkKhoBGv1draxubNF2M2m2lubjE6xjltvtcYWTOZTMIzQjAhTkfP2dDQiN8/PBUh9JyCYqI3x2RZpqysnHQ6zf33/3yU2dmyZStEk0IwZ7Df8V/YfnZnQeQoKbBue4Z0Zzexv/8aiUQCk5bFAvT2HmX79leNRCRdbveJT1xJdXUNqqoyb94Cw4BYVVUcDqfRWK6qqhpjFQLByZPfHBsp0xgrLry+vrFgKsLrHd0cEwhOl/zN4MrKKiwWCzt3vsurr75smPtCrjm2YMEi3G73SZ9bNCkE0x7bQw9CKl3wsV0mE4dNJvpkmaP/8Df0dXZRXl5h6DUHBqJYrVY6O7uNQsHv9xtfv27dhim9BsHs5GT1nBaLBUVRhZ5TMKmMTAJ45ZWXOH78GMFgzr8EoLW1nc2bL8JsNlNWVmaYnen3pWiOCeYSzn/7LnJe4lFMknjXbCagZem74yccrKsjPjjI+edfSHt7hyHlKC+vpKNjWG6nS0Lr6upFk09QFMaKCw8GAwXNMcDwourunm/UFiIuXFBsMpkMmqZhNps5fvwYb7+9w7gv9c3gyy+/iqqqapxOF3V19cazMbf55jvl5piojgXTklhsgL6+vlxk4u+eYSCbYdDp5JNDxcS7FgsfmM2oqSTlwSANS5dTVlZufP2FF24p1dIFs5Cc2dmwREMvGiKRcIFEY6SeUy9gXS5RLAiKz6FDBzl27FiBxlhRVC6//CoglwSQSiWprq6mu3teQRIAwLnnXlCqpQsEJSGbzRII9BnP8EzfCQJOJ0tSKZamUiSBbXY7zmwWNZOhpaISpbHJ+Lmprq5h69ZrS3sRglnDWHHhgUAupSseL4wL9/kUysoqaG/vLGhG6E1pgaBYJBIJ9u7dU1BbRCIRzjtvM21t7aRSKQ4dOoiiqHR2dqOqfqPmBWhsbKKxsWnC6xBNCkHJSKfThMOhgt3njRvPxWw288Ybr/PWW28C4NKg2majKpEgC8jA+YkEWwDJ4WBgzToSZ55VyksRzAL0HbKBgT527z54UnrOlpZCvwhhdiYoJmOZnQ0ODhpxhO+88xa7d3+A0+lEVf20t3dSUVFhfP3HP355qZYuEJSMfLmdrodWVZX58xeSzWb5xS/uMYwqqzxeKsIhnEM70z5N40+jURyahuZwcGLzxSCe64IJkkqlCIdD9PUdYvfug8Z9OV5ceHNzC4qiGFNuHo9XxIULisZYzbFgMEhXVzfd3fMZHEzw9NO/xWQy4fX68PvLaWvrQFEUAGpr67jxxlsmfZ1Fa1J0dXU9ALQAWSAKfKGnp+fNYp1fMHOJx+PGD0FzcysOh4N3332HZ599pmBkzePxEovF8Hq9zJu3gObmFlRVxZnJUPbQg8h5mlF9IFlDYvCKq6b4igQzmY/Sc7pcNgYGBrHZbKP0nLpxpdBzCopFodlZ7j48++y1mEwmXnnlJd5+ewdQ2BzLZrPIssyaNevZuPHcWW92JuoLwVhks1kikTChUBBNg5aWVgDuuedOgsGgcZzZbDF8psxmMxddtAWPx4vX68OTyeD89v+HPOTLIkGuQWGzkbj6OtGgEJw0mqaRSMQ/NC7c5bIRiyXxeHJeVHV1dQUbHQ6Hs9SXIZhFjNwM9vl8dHR0kU6nueuunxrvwfTmmCTlGmEej5drr70Br9dX0uZYMScpburp6QkDdHV1fRz4EbC8iOcXTGN0h3ir1Ybdbqe3t5cXX3xuVHzili1uGhubKC+vYMWKlXnxib6CkbWcf8Swh0Tkpz/De+PVoGnI8ThZux1Jlgn/6Ha0vHhQgUBnpJ4zGAyMMjuDnJ7T7/dTU1OLoii0tTWQzVoKzM4EgomSyWQIh3NvqGpr67Db7ezc+Qeee27bKLOzJUuW4fV66ezsora2DlX1j2l2dioGVDMcUV/MYZLJJNFo1PCVevHF59m3b2+B3K6srNxoUnR3z8dkMo0bn9jU1GL8Pf7Zz2F55SWs256GeBw0Dc3lItM1j+g/fH0Kr1IwU8iPC9fTufQ/ibzNNLPZgqIoQ3HhXUPTbg2kUiaRECcoKvpmcDabNTxx7rvvXo4fP2bUu5Ik0dU1j46OLiwWC5s2nY/b7UZVVex2R8EzUpZlw2enlBStSaEXEEP4yO14CGYZ+ohkPB7nnXd2GF1i3SH+nHPOpbt7PhZL7tYaGZ/odufitSorq6isPHmX69S6DQTeeBf7vXdj6tlJpr2DxNXXo5WVTcp1CmYGuZG1yBhTEYV6TrPZjM+nGGZnw2Y+o/WcFRUejh/vH/lSAsFJkUgkkGUZq9XKiRPHefXVl43mmJ5H/7GPfZyGhkYURflQs7NTfU7OVkR9MfvRawuAffv2sn//PuOZHo1Gsdvt3Hzzp41jFEUZGolXjUk3naVLT6F/ZTYT+cldmF97BduvfgmpNMkLLya1fiOI8fo5TSqVNOqJ/Em3kXHhTqcTRVFpa2s30rlU1Y/H4xm10SHqC8Hpks1micdjuFy5zYnt21/lwIH9BZvB5eUVXHXVNQA0NjbS2NhkPB99PqWgOdbZ2TX1F3GKFNWToqur6z+BC8hNzF1YzHMLppZsNsuRI4cN3ZyeuTxv3nxWrjwDgO3bXzPiE3WH+NraOgD8/jIuu+yKoq5JU/3EP/u5op5TMDPQ9ZyFCRq5f+fHJ9rtDlQ1X8/pN5pjQs8pKDaJRIL33ttZcF/GYjGjWQsQiUTy9JyqcV9CzoSvurqmlJcwYxD1xewhGo0aEeF6bREOh/jkJ2/BYrFy+PAh3ntv59A4fL0xcalz1llrirsgSSK96kzSq84s7nkF0578+MTCzY7AqPhEvd7Nf+OnKCp2u72EVyCYrRw+fIhDhw4QDIaGjCvDmM0Wbrnl0wCGV1rhZvDwBPqqVatLsu5iIuWPPReLrq6uG4Fre3p6Lj6Jw5uBPUVfhOAjyWazhEIhAoGA8cfv93PGGWegaRrf+973SKfTmM1m/H4/fr+fzs5OOjo6AIzPCQTFIGd2Fjfuxb6+PuPv/f39BSNrPp/PuCfz/4j4REEx0TSNEydOjLon582bx6pVq4jFYvzgBz/Abrfj9/spKytDVVVaW1spmz1TXi3A3lIvQucU6otmRG1RMhKJREFtEQgE2LhxI4qi8MYbb/DUU08B4PF4jOf3WWedhcPhIJ1OYzKZhNxOUDR0uV1+XaH/0eMTISe3G6u2UBRFeFEJiko8HufEiRMF92QwGOTmm2/GYrGwbds2tm/fPqreXbhw4Wx5Nn5kbTEpTQqArq6uOFDf09PT9xGHNgN7+vqiZLOTs5a5Tr5DvKZphoHUz352J8FgAACXywaYaW1tZ+3a9QAcPXoEl8s9Ss8pmDzmwihgvtmZLhcaT8+pqkpBzrKq5kbWJrM5Nhe+B9Odqf4eFCYBBPF4fCxatJhsNsttt/2QdDqNJEmG2VlHRyednV2GUdpIPedsQJYlysrcMM2aFHDS9UUzoraYVEY6xNfXN+L3+9m3bw+PPPKQcZzH48BicbJx47lUVVUxMBBlYGAAVVVFfOIUMVd+r+XiwoOMTEUKh8OG3A5yfj4jawtVVQvkdpPBXPk+TGem8nuQyWSIRCIFcuRVq87E4/Hw9ts7eO65ZwGwWCzGfXj22WtxOJwMDg5iMplm3WbwqdQWRbnyrq4uN6D29PQcGPr3JUBg6I9gCtAd4qPRfmN8+IUXnmPXrvcK4hN9Pp/RpNB1m6qq0t7eQH9/quCcYgxZMBFOR8+pj/WOZXYmEEyEfLOzdDpDW1s7AL/4xT0cP37MOM5sttDenpsWk2WZCy64CJfLNUrPCbmpHuHGPrmI+qL0pFIpIpEwFosVr9dLJBLmscceHRWfuH79xqGJogpWr16DquakTa2tdfT1DdchLpfb0FULBKeKHhc+Mp0rGAwQiw17Uenxibl7sN2Q2ymKiAsXFJdccyxX61ZXV+PzKezfv49HH32ooDnmcrmYP38BHo+HpqaWD613Z3tq18lQrPaMC/h5V1eXC8iQKx4u6enpEdsXRSZ/DHLv3t188MGugvhEk8nEpz/9x8iyjMPhHPKKGH7j5/V6jXPpzQrIxc+MbFIIBB9Fvp4zEAgU7FyMp+dsamouMDsTD2JBMUmlkvT3DycBvPrqy+ze/UFBc8zr9RlNiq6ueXR2dhnPyJFmZ01NzVN+DYICRH0xBWiaRiaTwWw2k06neeWVF0fFJy5fvpIzzzwLu92B0+kcFZ9ot+fkdm63m2XLhs0rhR+Q4HQYGZ+YH+uZ3xyz2Wyoqp+GhqYhHyplqN4tbXyiYHahbwbLsoTT6SISifDMM08SCgULNoPXrduIz5e7B5csWWZ4RSiKUlDver3egvdkgtEUpUnR09PTC8x8h45pRiQS4fDhgwUP6Egkwo033ozT6SIQCHD48CFU1V/gEK+TXyQIBBMhPz5x5O7FSD2nbnaWP0rp8/mEnlNQNPL9SQ4ePMDevXuMezIa7cdsNnPrrZ81ClSv1zvK7Exn0aLFJbkGwckh6ovJYf/+fQQCfXmTbgGamprZtOl8TCYTu3a9j8PhzItPVI2kGavVypYtl5b4CgSzBT0+caRMY2RcuMfjRVVVamrqjIkIVVVFXLigqOhJQ5lMhjfffL3gvkylUqxYsYozzliNzWYjlUpRX99YUFvojQev18vq1WeX+GpmNrNL6DLDGKnnzGUuB1i3bgNlZeUcPnyIp59+EpPJhM+nGA7x+sN42bIVLF++ssRXIZhNnKqes7Oz20jQGBmfKBAUg1hsgN7e3lH35bXX3oDD4eTo0SPs3PkuiqJSW1tr7Froxe0q4dgvmIOkUkmjAZGrLYLYbDY2btwEwIsvPk8g0IfD4URRFFpb26irqwdyzb8bb7xFPMsFRSObzRKN9o+KC8+PT4ThuPCKiko6OrrGjU8UCIpBb+9RI2FIb9bW1NRxzjnnIssyb775OlarDVVVjc3gmpqcFN5ms3HFFVtLfAWzG9GkmAJGxic2NjZTVVXFoUMH+fWvHzCOs9vtKIpqRCo2N7dw3XU34vF4xxxZEwWE4HTI13MGg4FR8Yk6enNMVcuEnlMwqeTrOUOhIJlMnO7upfj9fvbv38fTTz8J5PScquqno6PLaJotXbqcFStWieehYM4xMj4xkYgbEeGPP/4b9u/fB+RqBa/XS01NnfG1mzdfhN3uGDc+Ufw8CU6HVCo1Spqhe1Hlx4UPN8daCyRDIi5cUEz0zWC91g2FgpSX+1iwYAUATz/9JMFgwGiOlZdXUlWVmxiTJImbbrp11hlXziTE//kiobu8B4PBoTi6MqLRKA8+eL+h54TcTW+3O6iqqqK8vIING84p0HPmFwZ2u13kLwtOm1PVczY26l4RQs8pKD4jzc5qamopL6/g0KGD/OpXvzSOk2WZ+vpqY3etqamZyy/fiqqO3RwTBYRgtpPvEN/c3IIkSWzf/ipvvvl6gdzOZrOxfPlKZFlm8eKldHfPR1Vzz/KRPyf5kieB4FTIxYXnJyINb8L190eM4/TmmKKoQ/5owyPxIi5cUEzyN4NjsRiLFy8F4JFHHmL//r3GcXa7HYulzfj3pk3nYbPZxt0MFvVFaRH/90+RbDZLMpnEbrejaRrbtj1tdOj0+MSFCxezbt0GHI5cM0LXc6qqH6/XZ4ys2e125s9fWMrLEcwCxtJz6sVCfnPM7fYYek69WBirOSYQTIR0Ok0kEsZsNuP1+hgYiPLoow8bek6ds89eS3l5BX6/n9Wr16AoCqqq4vF4qa5WjIgwh8MpEjQEc4LBwUHMZjMmk4mDBw/wzjtvjZLbXX/9TXi9Xnw+ZWgc3m88z12uYbldQ0NjKS9FMAsYGReevxs9ODhoHKfHhdfU1DBv3rA/2ljNMYHgdMnfDK6pqUWSJHbseIO3336LaLTfqHdNJhMLFizCZDIxb958WlpajAABh8NREEGq++wIpifi6fER7N79ASdOHC+IT2xsbOLCC7cgSRInThzDbLbQ1tY+NBrvp6ysDMj9oJx33uYSX4FgNpCv58wVCsM7FyP1nIqiFpidCT2nYDLIZDKYTCY0TeOll14wCljd7GzRoiWsXbseu92Bw+GgpqZ2lNkZ5JoQwuRXMNeIRqPs2fNBwaTbwMAAl112BTU1tYYESlX9tLS0GTvQTmfu56a9vcOIyhUIJkIymRxj4jJIJBIuiAt3uVwoikp7e2fBVISICxcUE70hK8syR44cZufOPxj3pb4ZfMMNN+PxeLDbHVRXV6Mo8wqaY7pRe2tr27ivI5j+zPkmRSw2YJj36D8Esixz8cWXAPDmm69z/PgxY2StsbGJqqpq4+uvvPKaUi1dMAtJJpMcP37stPWcHo9XFAuConPw4AH6+k7kTeuEqKmpYfPmi5Ekid27P8BisVBeXklHRyeKolJRUQnkmrUiCUAw18hms6PMXoPBICtWrKKlpZX+/gjPPfcsNpttaBw+5xDvcrkBaGtrN2JyBYKJUuhFVdiQGBkX7vP5UBSV5uaWceMTBYJiEI/HOHDgQMF9GQ6HuPTST1BdXUM02s/+/XtRFJW2tnaj3tWl8F1d3XR1dZf4KgSTxZxoUuTrOfUH8rp1GwB47rnf8cEH7wNgsViMXWidzZsvwmazi5E1QdEYT88ZCATQtCQDA7kxypF6Tr/fb0xFCD2noJiMNPfVm7XnnnsBAK+88hK9vUex2x2oaq54ra6uMb7+uutuFM0xwZwkkUgUpHPV1NTS0tJKNBrlnnvuMo7T5Xa67rmiopKbbvqUiE8UFJWRceF6ckEqFSMUGm5GDMeFNwxJ7fxGfKKICxcUi5Hmvvp9uWjREpqamgkGgzz55OPIsmzUu01NzUYTor29k46OrhJfhaBUzKp33vnxie3tHZjNZl5//TVeffXlUfGJq1efhcViZcmSpcyfvwCfTxlzZE3f1RAITpVCPWfh7kW+nlNvjtXW1tLcXAfYhJ5TUHR0PWcgEDBGy884YzUATz31BLt3fwAMN8f0SQjQzaXs4zbHxJsswWwm5xAfIRgMYjabqaurJ5vNcvvtPy5IRDKbzVgsZlpaWvF4PJx33gVGKpLFUmj6ajabxfNdcNrkN8fya4tIJDKi3s01x7q6WpEku4gLF0wKI5tj5eUVNDY20d8f4c47f2ocpzfH9Hu0oqKSq6++Hp/PN2ZzTNyjc5sZ9xtSH1nLObRaOHjwAK+//ppRdOtUVlbi95dRUVHJ0qXLC0bi8x3i86UbAsHpUEw9Z76hj0BwOuQ3xxoamjCZTOzY8Qavv/6aoeeEnNnZsmXLsVisLFy4mLa2DlQ1N6kjkgAEc5FUKkU8Hsfr9QLw7LPP0Nt7lFAoaMjtGhubqKurR5ZlurrmYbfbDWPs/PhESZLEDqBgQujxiSNri/Hiwv3+ctraOoxaN785JmoLQTHQN4NBoqqqimw2y7333k04HCpoji1ZsozGxibcbg/r1m0ctzlmsVjw+/0luBLBTGDaNymi0Sg9PX/IcxUOkUql2LLlUhobm4Ccm3xDQ9Oo+ETIOVwLl2vBRNE0jYGBgTE0xoGC5li+nrOlpdXYRVMUVeg5BUUlmUwiyzJms5kjRw7z1ls7CAYDBc2xq6++Dr+/DJ/PZ+g59bHe/OZYXV19KS9FICgJe/bs5vDhQ8ZzPRrtR1X9XH31dQCkUkmcThd1dfUFjWWd1avPLtXSBbOIVCpFJBLOS+fSzbEL48JzDTE/TU0tRhqSoqjjxicKBKeDpmkMDg4akouXX36Ro0ePFDTHGhub2bLlEmRZpra2ltbWtoJ6V98MlmWZhQsXlexaBDObadOk2LXrfY4ePWq8+Vu+fCXd3fMZHEzwyisv4fF4jfhEXT8HUF/fQH19Q4lXL5gt6CNr+VFbeuGQH59otVpRVb9hdqYXr0LPKZgMYrEBPvjgg1FmZx/72MdpaGgkmUwSCJxAVf15ZmfDzdrm5laam1tLfBUCwdRz8OB+enuPGz83sVjM8FDZvXsXu3fvRlUVwyHe7y8zvlb3ZBEIikGhF9WwMfbIuHCPxzvkF1FXMAUs4sIFk8HBgweMJoR+X/p8PrZuvRaAQKCPbDZLY2OzsRmc/5xcv/6cUi1dMMuZNk2Kl156gYGBAXw+hfLySpxOFwCq6ufTn/7sKD2nQDARTlXP2d09v2CEUug5BcUklwQQGjXWu3jxEjo6uojFYjz33LY8s7N6oykG0NTUTFNTc2kvQiCYhjzzzNOEw2GcTieKokRpS2UAACAASURBVNLQ0EAmk8FsNrN+/UY2bTpfPMsFRSObzdLfHylIQho7LtyCoigFceGq6sfr9Ym4cEFRSSQSxsZbvlzoiiu2IkkSO3e+y/vvv1ewGVxWNtyEuOiij5Vw9YK5zLRpUlx22eXY7c5RI2uyLCPLokEhOHVG6jl1l+tQKEQ8PlrPWVZWQXt7h7FzMZbZmUAwEfLNfXPmUuW0t3cyODjIPffcaRzndrtRFBWzOVesqqqfT37yFtEcEwhOkQsvvBin022MLucjnu+C0yWVShY0IPLjE/O9qPTmWFtbW15toeLxeMSzXFA0stks0Wh/nmQoyJo1a7FYrLzxxnbefPN1IGfY6/PlpEJ6s3bNmnVs2LBJNMcE045p06Rwuz1ks1qplyGYgQzrOQMUxnqOrefMjcMLPadgcshvjsmyTH19A5qmcdddtxOJhI3jTCYTCxcupr29E4fDwfnnb8br9RXoOfOPFUlDAsGpU15eIWoLwWkxXnyi7l+iI0mS4UXV2NhUIAEdqzkmEJwu+c2x+voGHA4n773Xw7ZtTxnmvgB2u4OlS5ehKFa6urqpra1DVdUCc18dh8M51ZchEJwU06ZJIRB8GHp84unrOf3jxicKBKdDOp0mFosZkosXXniOw4cPEgwON8dqamqpr29AkiQ6Ozsxm60F5r75xUJ7e2dJrkMgEAjmMplMhkgkMqYEdLy48Pzawuv1ijhZQdHQNI14PIbJZMZms9HXd4KXXnqBYDBX7+pcdNEWmptbUVWVBQsWGZIhn08pqHf9/rICDwmBYKYgnqqCacVYek5dSzcyPlHXc3Z1dRcYBYqRNcFksG/fXg4dOlDQHHO7Pdxww01ALm3D4XBSW1todqazatXqUi1dIBAI5jw5uV2oQAKak2iEC7yoXC4Xquqno6Mrz4tKxeUScjtB8RkcHOTdd98Z1Rxbt24jCxcuwmQyEY/HqK6uZt68+QX1LkBFRSUVFZUlvgqBoPiIJoWgJKRSyVGmUh+u52wXek7BpDIwEOXEiePs3TvI3r2HjUbE9dffhCzL7Nu3h56enSiKmmd2NpzvvXHjphKuXiAQCASaphGNRsecihgdF55LimtpaStoLI+U2wkEE0HTNI4dO0YoFGTnzgT79h0mGAzS1tbOqlVnIkkSL730Ai6XC0VRaW/vRFVVamvrAFAUlSuvvKbEVyEQTD2iSSGYNE5WzynLMl6vV+g5BZNOvp5TlwytW7ceh8PJzp1/4JVXXsLlspHNmlAUhcbGJtLpNFarlbPOWsPatRuEf4lAIBCUmHQ6PeRFFRzVkMiPC7fZbCiKasSFq6qKzyfiwgXFRdM0BgYGCu5Dt9vNsmUrAHjooQdIJpN4PA7MZjuKouLzKUAu0v7WWz8rmmMCwQhEk0IwYcbSc+pjlMlk0jhO13Pme0XoMYpCzykoFrqeUy8UGhqa8Hq97Nr1Hk888ZhxnCRJeL1eYrEYDoeTjo4u6urqaW9vIBpNjzqvSAIQCASCqSU/LjwQCBTEheteVEBefGItiqIYUxEOh1NMXQqKRiaTIRzOGbWn02m6uroBuO++ezl+/JhxnNVqpaWlDcjVGhdeuAWn00VbWx2BQGzUeUWDQiAYjXhnKDhpRsYn6n9G6jndbjc+n0JnZ7fQcwomDb05ZrVacLncBAIBnnnmyVFmZ+eeewFer5fy8grOOGN1gZ4zvznm9Xrxer04HI6CSR+BQCAQTB65RKTIGFMRhXHhenxieXklHR2dIi5cMGkkEgn6+yOG18Orr77Mrl3vEYlEjHrX5XIZTYoFCxaSyWSH6l1lVFx4XV09gJjeEQhOAdGkEBRwsnpOk8mE1+sTek7BpKNpGpIkkUwmeeON7cZ9GYmEyWQyrF59NsuWrcBms2I2mw09p6r6jeYY5HSdK1asKvHVCAQCwdwklUoRDodG1Ba5f4+MT1RVNS8u3D9ufKJAcLrkp8IdOLCfPXs+GJoEDhKPx5BlmVtv/Sxmsxmz2YLfX05bW4fRGMs3xp43b0GpLkMgmLWIJsUcZaSeM5OJs3//YUKh0Jh6zoaGpqEmhDJkXCn0nILic/DggQK5UCgUpLW1nbVr12MymXjrrR14PO6h5lgriqJSXV0NgMvl5tJLP1HiKxAIBIK5ix4XPizNCA3VF0eIRvsL3hjqXlR1dfUFXlQiLlxQbAYGohw5cnhEcyzENddcj8fjoa/vBB98sAtFyW+OqcY0xLJly0t8BQLB3EM0KWY58Xh8zKmIkXrOmpoKHA4nNTV1Qs8pmDRyes5CI1WHw8nZZ68F4Omnf0s0Gi0wO9ObECaTiVtv/YzYSRMIBIISk81miUTChgFxvgR0ZFx4Q0M11dXVKMo8o7bw+RThRSUoGnpzrFAyFOKMM86koqKSI0cO88QTjyFJEh6P3hyrM+rbxYuXsmTJMlHvCgTTCPEbYhaQzWaJRvtH6TmDwSCJRNw4bqSeUx+H9/kUamv9HD8udPiC4pBvdpZMJlm8eCkAv/rVLzl69IhxnNvtoaGh0fj3RRd9DKfTOW5zTDQoBAKBYOpIJpOjfKjy5XY6I+PC9frC7XZTWekV9YWgKGSzWfr7I8Z9WFNTR1VVFUePHuGBB+4zjjObLSiKYpi319c3snXrtXi9PiwWy6jzitpCIJh+iCbFDELXc+qj8PruRTgcGlPP2draWuAVIfScgmKSMzvrJxIJU1/fAMCrr77E73//+wKzM7vdwaJFS5AkiSVLlrFw4aJxzc7Kyyum9BoEAoFgrjNWfKL+JxqNGsfJsozP50NRVJqamg2vCJ9PEXHhgqKSSuWaYzkvCD/xeJxf/eqXhMOhgubY6tVnU1VVxf/P3n3HSVKXiR//fKu6qqtz98xsXjawYViWKAKCBJEsAipKMMEJd+CpZ77zPP2d+TBwnp5ZPLNiPM6ECILggojoGkAcclrSstM5VHdXfX9/dE/v9E737OzszPSE5/16+XpJV3fV0zu7099+6vs8T19fP0cffUwrORaLxdpudDiOI39HhZhjJEkxy+w6PnGkqVQ6nSafz7WeN7qec+XKfaSeU0ybWq2GaZoYhsEjjzzM0NDdY5qdveY1/0AwGCQajbXVc470LxlZLOy777pevhUhhFiwRsYn7twRMdxaa4zuRWXbdqtXxOhx4YlEQnpRiSmjtaZer2FZNlprbr11S+vv5MiErf3338zxxz8fx3FIJpOsWrW6bb07kngIBoMcfPChvXw7bZTKYZp3o3UMz9sESBmJEHtKkhQ9sms95+hGgaPHJwYCFqlUkqVLl7Lffo16zr6+vjHjE4WYCvl8nkcffbhtp04+n+Pccy+gr6+fQiHP008/3arnHNnWO/J3cdOmzdLlWgghemh0ud2uvah2HReeTKYYHNzU2hXRaXyiEFPh0Ucf4Zlntrc1x166dBlnnHEWSikef3wbSimWL1/eWlsMDAwAjRtzp576gh6/g4nwiETeTSh0JVrbQB2tF5PLXUm9fkSvgxNiTpFvudNsovWckUiEZDLF+vUbWtvVRuo5ZbEgpspIPWfjbsXOZmdHHPEcVqxYyfDwM9x0042t5NiSJUsYHNyvVZax//4HsP/+B/T4XQghxMI2Um6369oik0lTKu0stzNNk0QiSV9ff9v4xGRSxoWLqeW67pjEmNaa009/IQB/+MMdPP74tlZybOPG/ViyZGnr9S972fm9Cn3KRCLvIhT6MkpVUGqkgexDJBJnk07fChzUy/CEmFMkSTEFJlPP2dgSn2ptWwsGgz18B2K+GannHCnLWL58BStX7sPw8A6+972rWs8baXY2Mull+fIVvPKVF0lyTAghZoFardY2LrxxB7oxPrFe31mi0dgOn2LVqjVt48Lj8YT0ohJTRmtNoVBo251z9NHHoJRiy5abuOeeIaCRHIvHE62dEADPf/7JBIPBeZscUypLKPSlUcmJ0cdcwuFPAlfOfGBCzFGSpNgDu9Zzjk5KjHQQhtH1nO29IuLxuNRziimjtaZUKpLJZAgELJYsWUKtVuWqq745JjkWCARYuXIfkskUJ5xwUtdmZ5Zlj2lmKYQQYnq196JqL7cbSSIrpYhGY6RSKZYvX9FaX6RSKRwnJIllMWXq9XorObZq1Wosy+LPf/4jt99+W1v/kmAwyGGHHY7jOGzefGBrukssNna9G4vFZvptzKhA4C60trskKepY1q9mPigh5jBJUnQw8XrOxmJhcHDTqF0RUs8pppbnebhuhXA4AsDNN9/I9u3b25Jj69dv4OSTT8OybFavXkM0GuvY7CwQCLDffpt69l6EEGKh2nV84ujG2LuOC08mUyxevJiNGwdbyYhEItlxfKIQk1UulwkEAliWxRNPPM7Wrb9vrXdHkmPnnHMuixcvIZXqY9Omza1yoVQq1TYufOnSZb18Kz3n+1HA63pc6/jMBSPEPLBgkxR7Xs850FbPmUql5I6zAMA07yYc/giWtQWtw1QqF1IuXwpEJnW+Bx98gKeeerK1tTeXy7FkyVJe9KJzAMjnC9i2zcaN+7UWCn19fa3XH3fcCVPxtoQQQkxCrVZtJSAymTTDw+nWuPDRvahCoTDJZHLMuPDRE5HEQubhON8kFPoMhrGdWu1AyuV/plY7elJnK5WK3HvvPa317khy7LTTzmDt2n3xfZ9CocDAwGI2bNjYal6ZTKYA2GefVeyzz6qpfIPziucdiNZ9QHHMMd8PU6lcjOQYhZi4eZ+kGF3PuXOCxu7rOfv6do5PlHpO0Y1l3UIicQ5QQanGLptI5HIc53uk078EwmNeUywWGB4ebhsBV6/XOeeccwG4++67eOyxR4nHE/T19bPvvusZGFjUev0ZZ5w5E29NCCFEF6PL7drLNHaOT4T2ceH77LOKvr6+1q4IGRcuuvOJx1+BZf0Kw2jcOLPtG7Dt35DP/yeu+4qxr/B9hod3tNa6IyVDBxxwIMcffxSuW+XWW7eMSY6N3ORYsWIl5557wYy+y/lFkctdSSLxkmbjzEZC0vfD1OsHU6mczzyveBFiSs2LJIXWmkqlPKF6zlgs3jY+Ueo5xeRpYrFLUarU9qhSFbR+gGLxUzzxxItbd9BOOOEkDMPg97+/g7vu+gvQqOdMpfro6+tv/T19/vNPxrZtSY4JIUSPeZ5HLpfrWAI6ely4ZVkkk6nW+MSRtYWMCxeTYdvXY1k3tRIUAEqB1mUM461s23YEmUyFTCZDf38/++23P55XbzXGHp0cc5xGMiyRSHDRRZdIcmwa1etHkcncTCj0X9j2r/H9OJXKxVQqrwBk97UQe2JOfXJ2quccyRhXKjsb1Ug9p5gJpjmE6z5DOm0yPGywfn2NUAi2brW48UYTz/sG5XJjMRCLxSmXS0QiUTZvPoB169bT19fXMTm2azNLIYQQ06sxPjEzasflSIlGtq0X1c5x4RvbGmPLRCQxlSzrG2QyJYaHTZSCdesad+W/9KUImYyD634CzxskELDYvHlz8zU2p59+BvF4omNyzDAMSVDMAM/bQKHw6V6HIcScNyuTFKPrOUfq5sav51zXVjsXi8VksSCmTKNOM08w6BAMBnnyySe47bZbyeX+gtYhlGo0pUwkfFat8liyxOPII6ukUnWUOn9Mcqy/f6DbpYQQQkyTXccnjt4VUSzurCNvHxe+b2ttkUwmZVy4mFLVapVisUgq1ej7cOutv+aRRx7BdR9EqSgAS5Z4rFvX2FFx8ME1DMMkGNxEOPzqMcmxNWv2nfk3IYQQ02DWJCnuuON2Hn/88Y71nCOLhVWrVrfduZA7zmIqaa1RSlEul7jzzj+3Soay2Qz1ep0TTzyFjRsHW5MyVq9+DqtXX0l/f4m+Pp94vFGusXy5z7JlPpXKiRQKi8a7pBBCiGl0551/5oknnmglJEaPT7Rtm1Sqj5UrV8m4cDFtRtYWAA899ACPPvpoKzlWKBQIh8NceOHFzedCMplk8eJjWbHiAfr6ivT17dzJc/jhVbRWDA+/EN+XBgdCiPlr1iQp7r//XpQypZ5TTDvf93niicdHNVFNMzw8zAEHHMihhx6G7/v8/vd3tOo5V67ch1Qq1RqvtWjR4takjVDon4hE/nNMXwqtg5RKb57x9yaEEGKnP/5xK57nk0ql2G+//Vtri13HJwoxFQqFAk8//VRbY+xcLsurX/0aAoEA27Zt4557/tbsjbaytd4dSWQ897nHAqDUsfT1fRelSoz+K6p1CNc9Hd9f3aN3KIQQM2NKvv0PDg72A18H1gEucB9w6dDQ0PaJnuPcc19Os2+gEHvN9/3WVJeRbb19fX0ccsizAPjpT3+E53kEAhapVJJly5a1xmyFwxEuueSyCSXHyuW3Aybh8BUAKOXheavJ5z+H78u2SyGE2Bt7u744//yXYxhyo0NMHdd1R03QaKwxjjnmeGKxGPfddw+/+c0tAESjUVKpPpYuXUa9XicQCHDkkUdx9NHH7DY5pnWcdPoGYrG/x7L+gNY2StWoVF5OofDhmXibQgjRU1P1ya2BjwwNDf0KYHBw8KPA5cDFEz2BUqo13UCIiapWq61FAsDg4H4AXHXVN8hms63nRSKRVnmQYRiceeaLiEZjHZudKaX2YPeOolx+K+Xy6zHNe9E6iu+v2ev3JYQQAtjL9UUgYOH7srYQe0ZrTT6fb5VlrFq1mmQyxQMP3M+11/6s9TzTNEkkklQqZWKxGOvXb2T58sb0ONseO81hT3YG+/4qstlrMYwnUOoZfH8NWkuJhxBiYZiSJMXQ0NAw8KtRD90GvHYqzi2E1ppisUixWGDJkqUAbNlyMw88cF9bs7NUqq+VpDj00MNQymjVGe/a7GzZsuVTHGUQzztgis8phBALm6wvxHSq1WrkcllsO0gsFiOTSXPdddeSyWSo19v7lySTKQYGFvGc5zyXVCpJKtVHLBZvGxcejUaJRqNTGqPvLwOWTek5hRBitpvyPZCDg4MGjQXEj6b63GJ+8zyv1azsgQfu58EH729rdmZZFhdffClKKUKhULNXRF9bs7MRmzZt7tXbEEIIMQ1kfSEmQ2uN7/uYpkmtVuN3v7ut1Rg7n8+htebZzz6Cww8/EscJEQ6HWbFiRVt/NMdpjO6Mx+MceuizevyOhBBi/lNTXWIxODj4aWAF8JKhoSF/d88H1gAPTmkQYtbLZDI89thjDA8Pt/6XzWa57LLLCIVC3HLLLdx555309/fT19fX+t/KlSvb7loIIYSYVmuBh3odBOzx+mINsrZYkB588EGeeeYZ0ulGU+wdO3awYcMGTjnlFLTWfPaznyUajbatLZYuXUoymex16HNYHfgJ8EdgCXAe0NfTiOAO4H8BHzgTOAqQRrlCzBK7XVtMaZJicHDwY8BBwJlDQ0PuBF+2Bnhwx46C1I320KJFMbZvz+/+iRO0az3nyASN4447gb6+Pv761zu56aYbW/WcI3crDjzwYEKhUNvIroVkqn8OYs/Jz6D35GfQe4ah6O+PwixJUkxifbEGWVvMClP977lWq7YmczXWFmlCoRDHHfc8AL71ra+RzWYJhcIkk0lSqRQrVuzD+vUbABbk+mI6f6caxoMkk6ejVA6lCmgdQinI5z+D654zLdccX514/EJs+5dABdBoHaJefw7Z7HeBsb1CZop8tvWe/Ax6a0/WFlNW7jE4OPhB4DDgjD1IUIg5bqSec2TU1po1a1m0aDGPPPIwP/vZj1vPcxyHVKqvVeO5du06VqxYOaaec8RCW0AIIYToTNYXC4/WmlKpSCaTIZ1OU626POtZzwbgmmt+yrZtjwGNtUIikWD58hWt155++pmEQqFWs+xdyfpiKmkSiXMwjCdRqrG5SakyALHYP1KvH4znrZ/RiEKhT2JZ17fiaMRUwrJuJRz+AKXS+2Y0HiHE5EzVCNLNwDuBe4BbBwcHAR4cGhp68VScX/SW1ppKpUw6nSYUCpNKpcjlcvz4x1e36jmh8cEfiURYtGgxixcv5vjjT2jtkAiFwm3nDIVChEKhXrwdMcsoNQyA1r3eGiqEmG1kfTG/eZ5HLpcjm02zevValFL87ne/5S9/+ROuuzMf5TihZkNsxcEHH8rmzQeSSqWIxxNjJmakUqmZfhsLViBwe3P6SKfqqzqO80WKxZkdmRoOfxrDKI95XKkKodCXKJXeA0jZsBCz3VRN97gLKfSa83zfp1arEQwG8X2fm2/+VXMO+DCVSgWAgw8+hKOPPpZwOMzixYvZuHGQVCpFKtVHPJ7AsiwAQqEw++8v0y5Ed5Z1C9Ho2zDNewDwvPUUCh+lVjuux5EJIWYLWV/MD67rEggEME2TRx55mL/+9U4ymTTZbBbfb3zBvfDC1xAOR0gmk6xfv7G1tkgmU0QikdYOiNWr1/TwnYjRTPOBrseUqhEI/HUGowHQKLW961GlyihVlFGuQswBUz7dQ8wd999/Hzt2NJpL1esltm17ijVr9uWUU07DMAyeeupJHMdh3br1rS7X/f39QGPW98knn9bjdyDmqkDgtyQSL2nbjhkI3E0i8TKy2R9Sqz23h9EJIYSYrHw+z0MPPTBqOleJp58e5pxzzmXx4iW4boVMJkMq1cfateta64tgsFGesWHDIBs2DPb4XYiJ8P3VXY9pHcDzNsxgNNDIZwaBzlVhWofROjKjEQkhJkeSFPNYqVQknU63FgqZTBrLsjj11BcAsHXrHezYsYN4PM6qVcvp61vK0qU7Z3Gfd97LexW6mOcikXe3JShGKFUmEnknmcxNPYhKCCHE7nieRzabaVtbpNNpDj/8CFavXksul2XLlpsJBoMkkynWrFnDvvvu1yr7lCTE/FGrHYXW/WhdQqldG9RalMuXzmg8pnkX4HU8pjVUqycjpR5CzA2SpJjjRuo5RxYKpVKJ5z73WABuuulGHnqoMYHNsiySyRSJxM4RW6ef/kKCQYdAICDdbsUM8rGs33Y9Ggj8CajSyw7cQgix0JXL5bYkxIoVK1i9ei35fI7vfOdbrefFYnFSqRSGYQKwZMlSLrzwNYRCYZRSsr6Y1xTZ7A9JJk9D6wqGUUDrIKDI56/A82Y2GWXbN9CtOkwp0Do+o/EIISZPkhRzhOu6rZFb69dvwDRNfve73/KHP9zRqucEiEajHHnkUQQCAQ499DAOPPDgMfWcIyKR6Ey/DSFoLCBMGnPVux2XOx1CCDHdGuPCc6TTjZ2Wy5evoF6v841vfJVyudR6XiAQwLZtVq9eSzye4KSTTmmWaSSxrPaEciAQGNPMUsxfnreRHTv+SjB4NYHAVnx/Ga57Hr6/bPcvnnIBuq0ftFZo3XniixBi9pFPkVlEa02hUMBxHCzL4pFHHuaPf/wDmUyaYrHYet6SJUtIJlMsXryEQw55VqueM5VKYds7FwujSzeEmD0U1epJ2Pa1Y7aHak2zcab8ahJCiKlSq9WoVCrEYo2GgTfddANPP/00mUyaer2RMF6zZi3Ll68gEAiwceMg4XBjmlcymWobF24YhpRriF04uO75uO75PY3CdV9AJPL/uhwN4bovmdF4hBCTJ98EeiiXy3HvvUOk08PNLZUZarUaZ531YlasWInWGs/z2Gef1c0kRJJksjFyCxodrqXLtZiLisUPYlm3AMXW6DKtDbQOUyhc3tvghBBijnvggft54onHW6UahUKegYEBXvrSxpdI160SiURYsWJlKxGRTO4c3Xn00cf0KnQhJs33V1Muv4ZQ6KsotXMnkNYhqtXnU68f0cPohBB7QpIU06her7N9+9OtRcJIbeezn30kGzcOUi6Xuf3221r1nMuWrSCRSLb6RkgSQsxXnreBdPpmIpEPYNs/RymN655MqfT/etANXAgh5pZCocAzzzxNOp1prS1ct8L5578SgPvuu5eHH36IVCrJ0qVLSSY30d8/0Hr9KafIdC4xPxWLl1OvH0g4fAWm+Si+v5hy+XWUy5ch04yFmDskSbGXfN+nUMi3JSGWLVvBxo2DuG6Fq6/+AdCo0UwkkgwMLCYcbnS4XrRoEZdccumYek4hFgLfX0c+/+VehyGEELNStVpt7bIcudlx4oknEwgE+POft/KnP/0RgHA4TDKZYvnylfi+j2EYPO95z8eyrDG9qISYvUbKP/f276zCdV+J675ybwMSQvSQJCkmqFarkc1mWmM8V69ei9aar3zlSlx35zxmxwm1GlKGwxFe8IIzSaVSRKOxVj3nCMMwMAxJUAghhBALkdaaUqlIJtMY6blu3TpCoTB33fUXbr75V63nGYZBIpGgVCoRj8fZf/8DWLduA8lkimAwOOa8o/tTCTGbBQK3E4m8uzn1y6BaPYVi8QN43vpehyaE6CFJUoyitaZcLlGpVOjr6wfghhuu5/HHt5HP51rPW7FiJatXr0UpxaGHHobjOK16zlAo1HqeUkrKNYQQQogFzvM8stksoVCIUCjEU089xZYtN5HJpKlWq63nxWIxVq9ew5IlSznyyKNaa4tEIoFpmq3nje4fIcRcZVm3kki8GKXKzUd8bPsaLGsL6fTN+P6+PY1PCNE7CzJJobVubYG8994hHnvssVapRqVSIZlMcsEFrwIadyOWLl3KfvttIpXqI5Xa2bgS4NBDD+vJexBCCCHE7DKyviiXy/zpT1ubZRrD5HI5fN/n+ONPYP/9D8C2bWzbZnBwU2s6VzKZJByOADAwsIiBgUU9fjdCTK9o9C2jEhQNjalfBSKRD5LPf6k3ge0lw3iUcPg/CAZ/DPhUqydRKr0LeFavQxNizpj3SYpsNsNTTz3VmqCRTqcplYr83d/9PUoptm3bxqOPPkwikWTdug2kUilSqb7W64855rgeRi+EEEKI2cb3fbZte6xtbZHJpNl//80cfvhzUErx5z//kUQiSV9ff6s0Y2Q0eCqV4swzX9TjdyFE7yi1A9O8r8sxH9v+2QxHNDUM42FSqeNQKodSHgDB4P9h29cBtwBrexrf7ORhWbeh1A7q/f/LswAAIABJREFU9QPxffkzEvMgSaG1plgsjpmgcfLJp+E4DvfcM8Qdd9zequdMJlOsWbOWer2OZVkcd9zzxvSKEEIIIcTCVq/XyWYzbWuLZDLFs599BEoprr32Z9RqtVbJ56pVa1i0aDEAjuNwySWXyfpCiAUmEnkvSmWaO0IaGqPWC8AbgJ/0KrRZKRC4jXj8VShVBBRK1ahWjyGf/ypax3odnuihOZOkGKnnHFkorF+/kXg8ztDQ3dx44y9bz7Ntm2QyRaVSxnEcNm3azLp1G8bUc46QBYQQQgixcJXL5dbawvd9Nm8+EIDvf/8q0uk00OgxFY3GWtO5lFKcddaLicViOE6o4xQNWV8I0Z3W/XjeWgKBoQ7HGg0056Jg8MdtCYoRjV8RW4ASEJ7hqGYnw9hGIvFiDKPY9rht/5pY7EJyuR/2KDIxG8y6JEWlUiGTSROJRInFYmzf/jTXX39tq55zRCrVRzweZ9my5RxzzPH09fW16jlHLxai0Wgv3oYQQgghZgnf98nncxQKBVasWAnALbf8mnvuGaJS2VkTn0wmW0mKww47HKVUs3FlEsuy2s65ePGSmXsDQsxDhcJHSSTOa+tLoTVoHW72cJiLquMc81Eqh9aSpABwnC+gVG3M40q52PYWDON+fH9dDyITs8GsSVJcd93PeeyxxyiVSgAcddRzOeSQZxEKhenrG2jVcyaTSZLJVGu8ViKR5MADk70MXQghhBCz0K9/fRPbtm0jm81Qr9cxTZOLL74U0zSJxWLsu+++rQkaqVSKWCzeeu2GDYM9jFyI+a9Wex7Z7PeJRN5JIHBn87HjKBQux/M29Di6ybLonqgwMM0nqdeXzmRAs5Zt/walOv9ZaW0RCPyFalWSFAvVrElS+L5m1ao1zYVCslXXGY1GOfXU03scnRBCCCHmmuHhHUSjUVau3Ke54zLV2m150EGH9Dg6IUStdiyZzK+BCmDS+JI/d3neUgKBR7ocDeD7iS7HFh7fX4zWI6Uwu9Jo3dfpgFggZk2S4tRTT8f3x9ZwCSGEEEJMxtlnv0TWFkLMCU6vA5g0pXbgOP9DMPgTwMD3TQzDa3tO48v4oEyuGKVcvhjLuh6lSh2OOtRqz53xmMTsIV2dhBBCzBjDeIxY7O8ZGFjCwEAficTpBAK/7XVYQgghxB4zjIfp6zuccPijWNZWAoGHUEqj9c7tAVpbzUkV3+hdoLNQrfY8XPc8fD+MbuaStbbROkwu9w0aO2smLhj8IanUsxkYSNLfv4pw+N1AcbevE7PTrNlJIYQQYn4zjCdIpY5tjmdr3GWy7VuwrLPIZq+iVjuhxxEKIYQQExeLvQGlhptjRhuU8tE6gOctRusErnsKlcpr6e8fBPK9C3bWURQK/4XrvohQ6EoM4ylqtSMply/D9/fZozOFQv9FJHJ5a1eGUhlCoc9h278ik/klYE99+GJaSZJCCCHEjAiHP4ZSuVaCYoRSZaLRN5FO/xHoWJwqhBBCzCpKZbCsW9sSFDuP1QGfdFp2Co5PUaudsFc3KZTKEol8CKUqbY8bhgvcRzD4f7juy/YyTjHTpNxDCCHEjAgGr+44bgzANJ/AMB6b4YiEEEKIyVEqz3j3exvHxXSzrJvQunPDVcMoEgxeNcMRiakgSQohhBAzZOzdpp0U4I1zXAghhJg9fH9Z1y/HAPX6QTMYzUI2/tph192bYm6QJIUQQogZ4bqnonXnRli+n8L3V89wREIIIcRkBSiV3orvh8cc0TpEqfRvPYhp4anVjkWpasdjvh/GdV8ywxGJqSBJCjEnNRrv7QBktNzCUiAY/Cbh8Eew7auBzh9KYnYqlf4FrcNtXc+hsZgrFD6M9KMQQvRWHaWeAsq9DkTMMNO8k1Do44RCn8A0753w68rlN1IuX4bWDr4fx/dj+H6MfP6/qdWOm8aIxQitByiXLx2TLNLawveXUKm8tEeRib0hjTPFnBII/JFo9M0EAn8GFJ63gmLxcqrV03sdmphmlnUj8fjLAVCqhNYRIEQm8xM8b9OMxqLUMwSDP0WpEtXqsXjeATN6/bnK99eSyfySaPTtWNYtAHjeGorFD8q/YSFED3mEQh8lHP5U846sj+ueRaHwMbTu63VwYlrViMcvwravB2qAIhL5IJXKSykUPsXu7+cqSqX3UC6/mUDgdiBIrfYcJjdNQmNZvyEQ2Irv91OtntEcXSp2p1h8P563jEjkCpTKAgaue3bzBsjYnS5i9pMkhZgzTPNuEonTMYydM48DgQeJxy8il/sy1eoLehidmE5KbSeRuKA1WqrxWAGtCySTZ7Jjx9+YqV9nodAniEQ+gNYmSnlEIga12nPIZq8CQjMSw1zmefuRzf4YKKNUDa3jvQ5JCLHARaNvwnG+i1I7d1AEg/9HILCVdPo2INi74MS0Coc/jGVd3/azhxqO80Pq9QOpVF47ofNonaBWO3nScSj1NMnkWRjGw83PRhul3kQu9wWq1bMmfd6FQ1GpvI5K5bUolWveyOreL0TMflLuIeaMSOQDbV9SRzTGF74DKf2Yvxzn63RquqgUQAnbvm5G4rCs64hE/gOlXAyjhFIuSpUJBH5DNPqWGYlh/ghJgkII0XOG8RiOc9UuX1JBqRqG8STB4NU9ikxMP59Q6HMYxtjyHqVKhMOfmLFIEonzMc17MIwiSlUxjAJKlYjH/36Pyk+EgdZJJEEx90mSQswZlnUDSnVORBjGExjGUzMckZgpgcDdY+Zfj1CqimnePyNxhMMf65goM4wKjvOD5hZDIYQQc0VjfGHnnXiN8YWSpJivlMqPSU6NZhiPT3sMgcBWEomTCQTuQKl6h2fUCIU+M+1xCDHbSLmHmEPG++uqxx0DJeY2z1uP1kGUcscc09rG8/aZkTgCge53M7S2MIzH8LzEjMQihBBiKgQYr2mv1pPpLSDmAq2jzbKKWpfjNo3xlp2nUu0ty7qFROIcoNTcGTqWUvVmHzYhFhbZSSHmDNc9q+vdjnp9P7Tun+GIxEypVF5F919XgRlruuh5y7oeU6qK7y+ZkTiEEEJMjWr1pK5fUn0/guueP8MRiZljUqlchNad1xdKaRzni9N29Wj0jSjVPUEBoLXC89ZMWwxiKtSBIlJ2PrUkSSHmjFLpnWgdR+udGW2tFVqHKRT+s4eRienm+8vJ5b6A1g5aOwBoHcb34+TznyYU+jzh8McIBO6Y1jjK5dd1mYceoFo9Fq0HpvX6E6VUDsN4gk59PIQQQuykdT/FYmM8cvvjIer1Q6hWT+lRZGImFItvo9uXS6VqRCIfxHG+jFLpKbmeUnkc57Mkk8dOsNeEQ7l86ZRce+/5GMaTKJXrdSCzglJPEYtdxMDAUgYGVtLXt5lg8Nu9DmvekHIPMWf4/grS6S2Ewx8iGLwapepUq8dTLL4bzzuo1+GJaVatns2OHUfhON/GNB+hXt+Maf6VePxiGl/GPcLhj1GrPZts9ntMx6QN1z0fy7qJYPD/UKqCUj6+H0XrAfL5z0359faUYTxILPYmLGsLYKJ1lGLxX6lULmHsdubp28IqhBBzSbn8NjxvHZHI5Zjm/fh+inL5HyiX/wn5PTm/GUaJxnphbL8pAKWyRCL/SjT6juakjbP34mrPkEodjWFs79jfajStARyKxbdTrx+xF9fsLhD4LZHIhwgEfgeEKZdfSbn8lg5NrTWO82UikQ+iVB7wqNWOJp//BL6/75jnNtZk8/vfjVIZUqnjmj/LRi8R03yMWOzNGMYzlMtv6HGEc5/SuudbU9YAD+7YUcD3ex7LgrVoUYzt2/O9DmPBk5/DxAWD3yMafUNzgbGT7zu47vkUCp+c1Hl3/zPQBAJ34DhXAQVqtZNw3bOZ3Ez0qaPUdvr6DkepDErt3EHh+2FKpX+mXH4LjYXGVwiHP4xhPI7WUSqViygW38VsmiMu/w56zzAU/f1RgLXAQ72NZlLWIGuLWUH+Pfee/AzG49Lfv3rMWqITrUMMD9+G76+d1JUWLfontP5m1/KinddReN4Gcrlv4nmDk7rW7tj2NcTjF9EYBz5y3SCetw/p9M1AtPXcUOiTRCIfakusaG2gdYLh4dvRegmG8RiRyLsIBn8M1KnXD6BYfD+12vOnJf7Jmqp/C6HQxwmHL+84Gcb3w+zY8QCzaV01W+zJ2kLKPYQQc1I4fEXHRUVj0sZ36HZXZO8p6vXDKRSuoFD4PK77MnqdoAAIhT6LUsW2BAU07hKFwx8BSkQi7yYa/VdM83GUAsMo4DhfJJl8AY2aSiGEEGIhCVKp/B1aT2T3ZZ1QaLI9Knzg2xNIUDTKWXO5b09bggJ8YrHXo1S5rR+GUi6m+Rih0JdHPbdMOPwfY3Z+KOWjVJFQ6DMo9RSp1LHNXaY1lNJY1l9IJC7Atn88Te+ht4LBH3ZMUDQEsKzfzWg885EkKYQQc5JhPDLe0RkbSavU04RCHyEefzmRyDt7Ns88GPxJx+knDSa2/UtCoc+PWWgYhotpDmHbP5/+IIUQQohZplh8L9XqiWgdQusA3TaZK1UjELhzklepA90TFI3kRIBa7UgymV/geeuxrJuIRl9LLPZqgsFvAZ1Hse+pxrSQbuUtFRznG7s8t1tj0SrB4E8Ihz+BUjmU8nY5XiYafSvzsz/WON1OJ3Rc7I70pBBCzEm+vxTDuK/L0Tq+v2jaY7CsX5NInAt4KFVBa4tQ6EoKhcupVF4z7dcfbfwxeZpAYCtaBzomMgyjSDD4farVF05fgEIIIaaEad6DZd2M1iGq1dNkutles8nlvoVp/g3H+RKO85UuI88DeN7GSV8DVtFth7vvryKdvgWtE4BHPP4KLOvG5g5JsO3riEQ+RDp9A1ovnmQMI1zGv089+r0HGH9qhUUw+L9dd4golcM0753GXSG94brnEwgMoVSn3RQ+tdr09BFZSKZsJ8Xg4ODHBgcHHxwcHNSDg4MHTNV5hRCik3L5jV0mbdi47osYXU85PSrE4xc0FxCNuxuNbY4VotF3YBgPTPP127nuy8fZrmrheat3cwap2xezj6wthBjNJR6/gFTqWCKRfyMafRv9/ZsIhSbXg0m087z9KBY/jNaL0LrTnXBFpfLivbjC+zt+TmvtUCz+ezNBAY7zFWz7Bgyj2CrHMIwihvE4sdg/7sX1G+r1g+i2u0Frm2r1BaOeewgQ7PLcEJXKKxh//aB2c3xuKpdfjectHXODSOswxeIHAKc3gc0jU1nucTVwHPDwFJ5TCCE6qlReheu+uLk900Br8P0o9fomCoUrpv36tn0N3T94PRzna9Mew2jl8oV43gq0bl9MaB0in/84tdoprQ7Uu/L9CK57zkyEKcSekrWFEE3R6Duw7RtQqoxhlJtfYitEIh/Ctn/R6/DmCYNs9odo3YfvNxIKo8s/kskXEwx+fZLnPrf5xXbnIyNrl2r1xNZjjT4PY8sxlKpj2zeh1PAkr9+6AqXSv4y50aO1QusQ5fLrRz1qks//15jkitY2nreMSuUiXPdstLY6XknryF7sPpnNomQyN1KpvAKtw2itqNc3kctdOeM7aeerKUtSDA0NbRkaGnp0qs4nhBDjMygUPks6fR2l0psoly8jl/samcx1BIPfJJU6jP7+dcTj5xII3DHlVzfNJ1Cq2vGYUjVMc7yeGdMhQiZzI+Xypfh+f3Mb8FFks9+jWn0Jvr+Mcvk1HRYlQTxvfdudEyFmC1lbCDGiiON8s+P2cqVKhEIf7UFM85Pn7ceOHXehtYPWtHYzjOyWjMVeR1/fIKHQR4DCHpz5Y5jmk7s0qwTDyBKNvr31mGFs73oGrS0MY8eevaEOyuU3Uiy+F9/va37Jtpv9MH6J7y9ve261ejbZ7A+oVo9G6xC+30e5fCmZzK/QOka5/Ca0jqF1+9dKrUMUCh9lvrZA1LqPQuETPPPMkzzzTIZ0+rdSNjuFpCeFEHOOh+N8mVDoUxjG03jevpRKb6NafVGvA+sJzzuIUumg5n/VSCTOJBDY2uq6bNvXYts3kctdSbV65pRdt17fhNZWx7pV3w9Rrx86ZdeaKK0TFIsfaG41HKtYvBzPW0s4/LHmIidIufwqisV/Rz4OhBBi9jLNbc2+Qp2PBwL37PU1DOMBIpH/wLavBRSueyal0jvw/ZV7fe65JhJ5D4aR7vjnrVTjRkU4/DEc53uk0zcysRLTT3VJMtUIBn9EPl8GQnjeRgzj9o5nUMrD81bs0XvpTFGpXEqlcgmGsQ2tI+P2NqnVjiGb7dxg2/eXkU7fRDT6r80m3D6eN0ix+D6q1VOnINa5QBplTjWlu7WwnaTBwcGHgBcODQ1NtP3tGuDBKQ1CiHlLA+cBP6W9M3MYeBvw3l4ENYt8C/gHoNjhWAp4Cui8JXHP+cAGGk2wdq3tjDUf75uia001TaMxls18vcMhpsxuZ5nPBFlbCDEMLKe9qeFom4C/7sX57waeQ2NnwMhnWgCIA3fQ+FWwUDwKrGO8aRw7hYB/B/5lAs916P7zc2j8ql0CXAO8lLETOELAxcB/T+BaveLRmGTSuY+FEE27XVvMmltnO3YU8P3511hlrli0KMb27fleh7Hg7e7nEAj8lmTypx1qFUto/WGGh1+B7y+b3iBnsUTic9h2pwQF+H6dXO4X1GrHjXuOPfm3YBg/IpE4C8N4CqU8tA4AFtnsd6nXLWC2/5uayAJs5snvo94zDEV//3Q3n51+srboPfn3PFUs4vHjse0bx0xS8P0wxeJlVCqd/5wn8jNIJF6HZeVRavS/lzpaZ3Ddt5HPf2Uv4587QqGvEYnQdddKuzL1+hdJp3ff0HLRovXAXR2P+b7Njh02jXXDMTjOu4lG39NcV/gopalWTyKXew+zf20B0Lkcttfk91Fv7cnaYtYkKYQQu+c43wU6jTsCrQ1s+2dUKhfPbFBTzDAew3GuxLK24nmrKZcvwfMO2v0LAaU6Jyh2Hu88F3yyGiPDtmJZWzDNe/D95VSrJzF1uzXE7FEnFPoUodBnMYxn8P0VlEpvpVJ5NbLNUwgxE/L5z5BKnYRS2zGMYrPRYZha7SQqlQv34swulvXrXRIUDUr5BIM/IT/nv9f52HajZ5VSRarVU3HdC9A6NuaZSqW7jtTspPMYyk7ejdavGbMW8f0Q5fI/MvprWaXyOlz3Amz7WpSqUKsdg+dtmHBMYu4wzb8RibwX2/4loKhWT6FY/H8L/uc9ZUmKwcHBTwIvAZYC1w8ODu4YGhraPFXnF0IAlDsuIqBRpzgyCnOusqwbSSQuAOooVUVrE8f5DsXiOymX37jb11erpxEI3NWxT4RSVWq1w6chakWtdiy12rHTcG4xO+jmzPpftXqdmOZDRKP/gmneRbH4kR7HN3/J2kKInbRezPDw7wgG/xfbvhatI7juBdRqR7N3yVKP8cdE1pvH52pCtk48fj6WdQuG0biZYdu3EA5/lEzmBnx/n/Zn14/A96MYxu6bYmptUq2eMME4zqNY/DORyBXNHRIapTxc9xxKpbHlIlr34boXTPDcYi4yzbtIJk9CqVJrfW/bP8aybiCTuXGeTkaZmClLUgwNDf0T8E9TdT4hxFjV6mkEg//b+pBtZ1KtPm+mQ5pCFeLxV7bdYVDKA8pEIh+kWj0Vz9tv3DOUy5cQCn0WqLYlc7QOU6m8fNymUEJ0EwjchmXd3EpQjGh01P8K5fLr8P3VPYpufpO1hRC7CuK65+O650/hOcN43kYCgbs7Hq3VjmDuJijAcb6KbW/ZZX1RwjBcYrFLyWZ/1vb8avUUfH8xSlXaRnePnvSx8zGHcvktE46lXH4Hlcol2PYvUKpOtfo8fH/V5N7YHjDNvxCJfAjLugWtHSqVV1AuvxGtk9N+bdFdNPoOlCruMvHFBwpEIu8ml/tOz2LrNemYJsQcUq2+AN9fidZ22+ONcZPH4Xlz9wZjo5t4tzs5dRzny7s9h9YDZDLXU68/C62D+H4M3w9TLl/aHIMlxJ4LBn84TqmQJhj8WZdjQggxNxQKH0Tr0JjHtQ5RLL6vBxFNnVDocx1/hyvlYVm/Q6mndzlikslcS612OFo7+H4crR08bxW+H8X3o2jtUK8Pks3+ZI+35Ws9gOu+nErl1TOSoLCsLaRSJ2PbP8MwMpjmk4TDnyKZPB6lsh1fY5r3Eon8M4nEC4lG34JpDk17nAtPDcva0mWCjMa2r2P8HU7zm/SkEGJOCZDJ/IJo9E3NL0aNhkqNMZIf7HVwe8Uwnm67YzGaUnUMY9uEzuN5G8hkbsQwHkepNJ63lsb0EyEmR6la1zKrxgLCm8lwhBBiytVqJ5HLfYVo9J8xjKcAjeftQ6Hwn9Trz+l1eHvFMJ7pekxrG8PYgect3uXxJWSz12IYD2KaD+F5q/H9fYEqpnkfWkfmyA46TSz2j2OSNEq5mObjhEKfpVR6R9uxYPD7xGKvo1F6W0PrW3Gcb5LPX4HrvnIGY5/vfMZPQowcn7u7mPaGJCmEmGO0TpHPf5VCIY9SO/D9JTTGUs1t9foBaG12zCj7foh6fc/6Sfj+chrj2gQUMM1H8f1FaD3Q62DmnGr1BQSD3+1Sn2w2m6UKIcTcVq2ezvDwac2bAkbzc3Tuq9c3Y9s3dzymVB3P676bwffX4vujx6/aeN7+Uxzh9DHN+5tJp7GUcgmHLycU+m9qtWMoFt+F7y9vJjUqo55XB+rEYm+mVjuxbYqcYTyKUiU8b1+kafieClKvH4xlbe14tFY7ioVc9LBw37kQc5zWMXx/DfMhQQFQrz8H39+n2UxqVwEqlfbsvWE8gm1fQyDwW3bOdBftXKLRNzMwsC/J5In0928ikTgbw3ii14HNKdXqSXjeRrRun/veKLM6ebe9UoQQYu5Q+P7KeZOgACiV/qVrKUu5/GogMupRD8u6Bdu+BsN4chqiKWMYjwBTO22sOxetza5HlfIxjDy2/XNSqZMJh69A6+537oPB7wIQCNxBKnUEfX2HkUw+j/7+fXGcz7GQyxMmo1C4fJwyq/f3IKLZQ3ZSCCHamObfmo2VwlSrp89gUyVFNvsjEolzMIz7aWxvMwCHbPa7o5peFojHX4Nt/6rZm8NH6zi53Nf3eLdFIPAnQqGPY1m/x/f7KZcvBfZshKtSeUxzCK2TeN76PXrtdIvH/w7b/mWz+VfjMcv6NcnkiQwP/575kuCafgaZzE+IRt+J41wFaLS2KZf/nlLp33odnBBCzAEutv0LDONJPG9z8y7xzGxjr9WOJZ//KLHY25s3QnyUquO6Z1Asfqj1PMu6gXj8YqAKKJRycd0Xkc9/GrC7nL2TKo7zdRznfzCMHNXqMc0Ro19jYOBraK1QyqdSeQnF4kc7jkEFMIz7MYx0M0ken9R7b0yH6J6kGNEoaSzhON/uOlJVKRfDeBLTvIdE4sxWE/eR9UU0+h5AU6m8dlKxLkT1+lFksz8gGn07pnkPoKnXN1MofJR6/dm9Dq+nlNY9z3itAR7csaOA7/c8lgVr0aIY27fP+SHYc15vfw5l4vFXYds3N7PoBkp5FAofolK5ZAbj0AQCWzHNv+H7S6nVjmf0B2w8/lJs+6YxY0Z9P0o6/fu2bYjjse2fNBcjbrOTMvh+GMM4me3bv8ruN5rViUTeRSj0P2htNbeMriaX+xKed+DE3+40Mc17SaWe23Esre9HKBQ+huu+ogeR7d7s/n1URalcM3k3f/P8hqHo748CrAUe6m00k7IGWVvMCrP73/PC0OufgWVtIR6/gEZyoIbWJr6/kmz2/7ru2DCMbdj2j1GqQq12LPX6YVMQSQHbvgGlStRqR7X1lDDNIVKp48Z8Qdc6RKXyUgqFT0/wGlWSyTMwzT+3JkJp3VhPKBWgkQAZOXeQen0zmcwNjF5zmOZficf/DtN8qLm+qFIuX9hMqOx5SYXjfJ5o9N/HaQC9k9YWWlsYxtjnNtYO/4VtX08w+P3mBLZdn5Ngx44HJhXnTOj1v4XxKJUBFFoneh3KtNmTtYWUewghAIhG34Jt34xSFQyjjGEUUapCNPpvWNavZygKD6hSrz8L1305tdrzGZ2gMIwHmjG6Y16pVA3H+eIEr+MSi12GUuVWgqJx/hJwfXPSyPii0bfjOF9u/nnlUaqMaf6NZPI0DOPxCcYxfRq7YTr/ijeMIrZ9zQxHNF/Yzb4e8zdBIYQQU8UwniSReBmGkW1+VlYwjCKmeR+JxIvoVB4QDn+Ivr5DiEb/H5HI+0gmzyCReAF7VyJRAUJUq2fhuuePaXoZCn2C0QmEEUqVcZzvotSOCVxDEwp9vi1B0TiH31xrtJ+/0bxyCMu6adRjT5FMnoJp3o1SZQwjh1IVHOdrRKNv3oP3u1OlcimFwgfw/T60DjP+/WkLraNj1g+Nm1dhXPdsLOtXHRMUDR6mee+k4lzotE7O6wTFnpIkhRACpTI4zvc73nWHMuHw9I7vNIxtxGKvYmBgMQMDS0ilDsW2fzzmeYHAn9C6c3ZeKRfLumVC17Osm+leN1nEcb4y7uuV2oHjfKNtEdJ4vBGH43x2QnFMJ60duv2K11p13V4qhBBCTJXG+PCxk7uU8jCMRwkEbm973LZ/Qij0SZRym6WKdZQqYVm/Ixp96x5fPxj8Hn19BzIwsJSBgSXEYhd3GDkKlnVb1y/eWgcJBO6ewHU2EYm8a8zaYDxKFbHt61v/HQp9ofne259nGGUc5zsotX3C5x6tUrmEHTvuY3j4FqrVF3a9iaF1hEzmWjxvLb4faY1c9f1VZDLXAA4Q7PjaxvvxOvZYEGJPSZJCCIFpPtzs7zCWUmCa43847w2lniGVOo5g8CfNUY8+gcD9xOOXEAx+o+25Wqe6nkdr0HrRBK/ZaUrD6OOd54aPCAS2jmmiuPO1VYLBX04ojulUrZ7adaSr1mFc94JxXx8IbCUU+gSO87kJj38VQgghRgsEtnbc/digCQT+1vZIOHxFx1KDxg2AH6BUbsLXdpzPEY2+HtM1SLl3AAAfiklEQVR8uLmboUow+L/Nso5MeyS6b5wz1fH97uuPYPCbxGKvxzQfH2dcdTdm23rCtq/v+ueldRDLumMPzz9aAN9fR7H4nq7NGguF9+H760in/0A2ezWFwhVksz9gePjPzf4WmkrlRfh+5zWQ563YZRrKrkoEg1cRCv0ntv1TOiWwhADZryqEAHx/CUqN3eY4+vh0CYU+g1LZMXcwlCoTjb4T1z2PkdrGWu0YutU5ah2mXJ5Y08t6/dnjvN/QbkdKNnYhdJ8o4vuTa3A1lbROUSi8r1mHuvOuju+HqdVOpFY7tssryyQS52FZtwM1GuU276ZUejOl0jtnIHIhhBB7xse2f0Qo9HkMYzu12hGUy2/E8wZ7HRiet7o5XrzTLgVjzPrCNB/oei6tAxjG43jeRD5jy0Qi7+2w47GOUmkc5yuUy2/a+ezy32Oad3bpxbB0nLGjHtHou7o2m9w9G9d9ceu/xm+QqadkF6TnbSSb/RnR6BsJBP4KmPh+gmLxvaNuYCjq9SOp14/cGal9DdHovzRLWqvNBqC6GXej0Xk+330nqWXd1OxNAkpV0NpB6yjZ7E/xvA17/b7E/CI7KYQQKJXuWqfo+2HK5ddN27WDwf8dJ2FQJxD4y6j/DpDLfa0Z685kRWNnwDnUas+b0DV9fx9c94wxdxIaNZcOlcrfjfv6Rsdlp8u5I1QqF00ojulWqVxGNvttqtXn4vv91OubKBY/TC73Vbp1VY9G304gcBtKlZo7WyrNWeqf7FiCI4QQopc0sdjFxGKvxbZvIRC4B8e5ilTqeCzr+t2/fFr5zS/V3foX2GNuCow3+lSp2oRvmjR2HHTry1QmGPx+22Ou+1JqtePReuc4Uq1tfD9KPv8Vun1mmub9NPpdjK8xVaT93rDvh6lUXtLWbLtSuQjfD3c5S4Ba7Tm7vdZE1OuHksnczI4ddzM8fAfDw38bd4elbV9DPH4RpvkQSlWb5a0arRW+n8R1X0Q6fWNbUmM0pbaTSJyPYRQwjAJK1Zv//ykSiTPp/ndELFSSpBBigTPNO0kmn49S6bYayEb5RIhq9YzmbobpsrsRZO3Ha7XjGB7+DeXyxdRqh+K6p5LLfY1C4VMTONdO+fznqVReitZBfD+O1qHmnZJbRo077cYkl/siWofa6jp9P9xs+vnSCccxvjKdGnntiVrt+WSz17Bjx4Ok07+lUrmQ7uPICjjOdzGMsQsupUqEwx/bq1iEEEJMLdv+Bbb989Y4SBjZLVBqTrCq9Sy2aPQNzd2S7Y9rbeD7UbLZ77DrF/dS6Q1oPfZLutY21erJ45Z9ttuztUXjc/3b5HKfo1o9gVrtUEql15NO30G9fkjXs2gdaGvAPfa4QusQ5fJlwJXU64PNtcJ6isXLx0wNcd0XUa8f2fZnoLWB1iHy+S8wNZvgfaBAY2fGInx/H8b/SqiJRN7RdbdIrXYk+fxX8LxNXc/gOF+nUyJCKY1SOWy792WyYnaRcg8hFrho9F9RqjhmEQFQq20mn7+S6Zxl7rrnYJr/1aUG06JeHzvO0/fXUix+ZC+vHKRQ+DTF4vsxzXvRuh/PW8+iRTFg9+OparUTSadvIBy+Asu6Dd9PUqlcQqXyKvb2V6tl3UA0+k5McwhQVKvHUSx+pFkPOn1M84nmgqvb8e7bcIUQQsw8x/lyW4KiXR3L2gKcNZMhAWCa9+A43+vYkFtrg1zu6x3vurvuBVjWFhznB4yMCG80blxBPv+pCV+/Vns23Rpkax3Cdc/tcMSgWj2bavXsCV/H99fi+0swzYc6XMeiUjmHYvEKtI4RDsdIp1+ymzOaZLM/wHG+heN8HsNIU6sdQan01ikYb14iEnkfjvNVlHLROkap9AbK5TfT/eYFKDWMaXbuTaWUxrZv3u2VA4E7uzRnb/TyakwEOWUib0IsEJKkEGJBq2FZWzp+KVUKLGvrtEdQLl+G43wVw3imrdFjo4HTR5juX1Na93Xdnrg7nreZfP5/pjQe2/458fiFbXcsbPtGLOsE0uktu2lItXd8fxFKdb/rNt42XCGEEDPPMIbHPb67RtDTxbZ/Rrct/Er52PZN1GondjpKofAZKpV/IBj8PkoVqVZPpFo9jT1bDzgUi+8nGn1n2+ep1ha+P9DcVTgVFPn8J0kkzgPKrfXUyHWKxf+YRB+JAJXKq6lUXj1FMQL4JJNnNcejNpIFSqWJRD6Kad5DofCFcV5r0n0iGmjdPcExwvPWobXdsbxXaxvPW7Xbc4iFRco9hFjQNON98Oz++BREoPvJZG7GdV+K1jZaK+r1/cnlvjrNZSazkSYaffuYLZWN7ZAlwuEPT+/VdZJq9dSOk158P0yp9E/Ten0hhBB7plo9vjlyeiylqtTrz5rhiEZ4dF8/aHY31aFeP4Ri8QMUCh+nWn0hk7lhUalcTC73Rer1jc0SVodK5XzS6Zt306Byz9RqzyOT+RnV6vPROtTcWXkR6fSWCZSPzgzLugHT/OuYck6lyjjO1ZjmfV1fq3Wy467WxjET1939zpNGwqXb106LavXU3Z5DLCyyk0KIBc2mXn9W15FWtdpRzEQu0/eXks9/gXz+8zQWLwszf2oY2zCMpzoeU8ojGLyGwvjTU/daPv/fJJOnYhiPYRiFVsdu130xrvvy6b24EEKIPVIuX0Io9BmgsktfKYdq9RR8vzd3qKvVk4lEPkKnZITWYarV02cojrOoVs+i0YdBMV3lq/X6YeRyV0/LuadCMPgjDKPbAkJj29dRLq/v+vpC4T9JJl9AY7fIyEQPE60TE5r85fv7kM9/lljsHwEfpdxmg9AA2ez3gbE3R8TCJkkKIRa4QuE/SCbPGnP3XusQxeL7Zzia6VtAzA29f+9ap0inf4Nt/xzbvq45OeVl1OuH9jo0IYQQu9B6CZnMNcTjr8YwngQCKOXiui8kn//0bl8/XTzvIKrV52Hbv9ql3MKhXj+oOVJ8Ji3Mmx87GWhNl55TqjndrLt6/Vmk078kEvkAtn1jawdFqfROfH/lhCJoTGE7mmDwm5jmw9TrB+K656F1Ys/fjpj3JEkhxAJXrx9JJnM10eg/Ewjc1XzsQAqFjzRHbYqZ4vvL8bwVBAL3jzmmdQDXnanmZybV6hlUq2fM0PWEEEJMlucdRDq9FdO8C8N4hnp9f7Re3OuwyOW+Tjj8QUKhLzZ7EQQol19Fsfg+ZkNSfjIM41HC4Y83e24EqFReRrn8+llT1tGN676YYPA7KNWpyapu9vwYn+dtJpf79l7F4fvLKJfftlfnEAuDJCmEENTrR5HJ/Bql8s1serTXIS1QikLh4yQS5+1y58lA6yil0j/3MDYhhPj/7d19lCV1eeDxb1Xdl+57u+me6RkFFEJwofA17hiPmhXzTgzRDUp8ISQgRncTd5NDEpbo4ktINMsRTzYqRFE3WYILJ5uDgB51Y1B388JuNlFYF4nlaFBQ3IjNTPf0fb+3av+4l2GG6Wamp+90Vff9fs6Zw0xVnV89PUVPP/ep3+/5qbgCBoNnMVi9V2VOKjSbV9Nsvp0gWBr1gdi6Hz2iaO9oy/bmwSbTtdr7mZq6mX37/qoQhaG19Hovod//Qcrl/31YfpGmNTqd15KmZ+QXnLSKSZ/7JOkQww7UFijyNGzAdTvd7gtGxYkync7Psm/fX472MpckaSuJyLKdbOUCBcDMzG8QBMuH7YIVBF3C8HvU6+/MMbJjEbC0dCvN5q+RpjvJMhgMTqXRuJqVlf+Yd3DSEbb2vxaStA31+y9iaekveKwz+tacFitJ0vawQrl818GmkYcKgh7V6q2srLwvh7jWo0KzeRXN5lUM8wtzCxWXRQpJKiwTCEmS8hYEHZ7oZ/Lw/FZifqFic7mHJEmSJK0hy3aSpmv3nOj1bDQujZNFCkmSJElaU0Cj8btk2fQRZ4Zbtr8jh5ik7cvlHtJhWlSrt1Eu/z2DwSl0Ohcd8/7PkiRJq4mivVSr/5Ug2E+vdy7d7vmYhm8tnc6FQJuZmauALkGQkqY7WFl5L/3+i/IOT9pW/NdRGomirzI//1KgRRg2yLIK9fq1rKxcQ7v9+rzDkyRJW1CtdjW12vVAnyDok6b/hSzbxf79nyFNT847PK1Dp3Mxnc5riKKvAiUGg7Owv4PGp021+gmiKCFNT6XTeSVZNp93ULmwSCEBkDE3dyFBsHiwc3MQdAGYmXkLvd4LGAyemWeAkiRpi6lUPsP09AcIgvbBY2G4Qpa1mZ29jKWlT+cYnY5PicHgGXkHoW0miu5jfv5ngA5huEKa1piZ+fcsL99It/tTeYe36exJIQGl0t8eVqA4XJfp6Rs2PSaNQ5tq9WZmZ9/IzMwVlEpfzDsgSdIEmZ5+P2HYPOJ4EPQpl79AGD6YQ1STJwy/zuzs61hYOIWFhZOZnb2EKNp73ONF0V5qtbcxO/t6pqY+QBDsH2O0mjx95uf/JUGwSBiuABCGTYKgyUknXUoY/r+c49t8zqSQgCh6YM1zQTAgir62idFoHMLw28zP/zhBsDx6axUyNfVR2u3XsLLyB2zv6ZkZ0ACmgSjnWCRpckXRN9Y8l2UVwvBbpOlpmxfQBIqivczP/whB0CAIUgCq1Y9TqdzJ/v2fZTB4+rrGm5r6Q2ZmfhsYEAQ9KpVPUa+/i6WlT9Lv/8D4v4BC6Y1+1fIOZFupVO4EmgSrpqYDqtU/odW6cpOjypczKSRgMDiT4Qe7I2VZmX7fpR4nShjeT6l0N8MP1eMzO3sZYfhPByvSQZASBE2q1T+lUvn4WO9VHBnT09exsPA0du06nV27TmVm5nKC4EDegUnSROr3zyJbPb0gCDqk6RmbGs/kaFEq3UMUfY16/SqCYOVggQIezQka1OtvWdeoUXQvMzNXEwRtgqAHDN94h+EyJ530c0D6xANsQeXyXzA//2J27drJrl0L7Np1Cjt2PI9KxaVK4xJF/3hwmfnjBUGHUukfNjmi/FmkkIB+/3mk6VPJstW+JUq02/9q02Pa7qLoy+zY8SJ27nwhc3MvY9euM6nX3woMNjx2GD5IuXwPQXDkWGHYZHr6/Ru+RxHV61dSq72TMPweQdAnCFpMTX2UubmXMnzzIUnaTK3Wr7PaW+csq9DtnkuanrL5QW1rGdPT17CwcCZzcz/Djh0/RKXy31ZdzhsEGZXK/wD6xzz69PSHgLU+TDYol//yOOMupqmpG5ibu5hy+UujvGL491Yq7eWkky6lWr017xC3hcHgDLKsuuq5LKsyGMSbHFH+LFJIAAQsLd1Kmj6FNJ0hy0LStEaWTbG8/IFR92aNSxh+h/n584iiLxMELcLwAEHQYnr6w9Trbx7L+FlWWfN8FD204XsUTRg+xPT0fz5i7XMQdImif6RS+WROkUnS5Or1zqXReCtZViVNp0b5RZ1+P+bAgY/kHd62U6v9B2q1PyAMG6Pcor3GFPpHZaxn9kMUfWPVFyCPjhWG2ye/CIIlZmbedljT18PPt6nXf4vtOHtks3W75wGrFykgpN2+ZDPDKQR7UkgjaXo6jzzyJSqVz1Aq/V/SdDedzgVk2Y68Q9t2hk2mOkckDsNCxY00m28hy3Ye9/iDwZkEQWfVc1kG/f7268pdLn+OLCut+nWHYYNq9Ta63QtyiEySJlur9W/pdH6OSuV2wvAAvd4L6fVezPbujZSHJrXa+wiCIxuVrmXYQ2LtlxqP1+s9l3L5rlWn5gcB2+qNd6Vy5yivWPuaIGgQRV9lMDhn8wLblkrs33878/MvA3qEYYM0nSYIYHn5P5Gmp+Yd4KazSCEdJqLb/Wm63Z/OO5Axa1Kt3kEUfZPB4Aw6nZ9l2FQxH9XqnWuuvcuyCqXS3fR6P37c42fZLjqd86lWP7XKh/YardZvHPfYxXW0ZNdkWJLykqYn027/ct5hjF0UJVQqnwJSut2fZDB4Tm6xlEr3kWXRUWZOPCbLpmk0fm9d92i330CtduSOb1kWMRicQb+/Z13jFVubtfq1PSbD/GI8BoPnsLj4FarV2yiVvkyanka7/WqybCHv0HJhkULa5kqlv2Vu7kKGXagbZNkMMzP/jqWlj9HvPz+XmLJs5onOkmX1Dd9jZeU6wvDVlMt3A4PR24A+KyvvpNf7oQ2PXzTd7k8QBKuvq03TOp3OqzY5IknS9pUyM/NvmJq6lWEvqZR6/d10uz/K8vJNQHnTI8qy+hMsxWC0DHT4oXowOJOVlWvp9f7Fuu6RpqezvHwTs7OXAgFB0CXLyqTpqSwt3cp2+sDe6527Zl7xqCybZzA4e5MimgQ1Op2L6aw+GXiiWKSQtrUV5uZeSRg+trtDEAx3u5ibewWLiwmw8YLAerVaryOKvrTq3vFQHUvxJMtmWVr6NKXSPZTL/5M0naXbPX9Dy0iKLMueTLP5K9RqHzpsqmuWTTEYPJ1u96U5RidJ2k6mpm5gauq2x/UraFGpfJ5a7fdoNt+x6TENBueQprtW3VZ+OGviHbTbr2X4MuT43053u+exuPh1qtVPEoYP0+8/i17vXLZTgQKGBZl2+xVUq7cThkf2pciyKVZWfp/t9nWrGCxSSNvY1NTHWHu3jAHV6u10Ohdv4A6PTgN8oh9QKWH4TaBMmj4VgE7nVUxN3Uip9H8OFiqGO6tUOXDgg0C0gZgO1+8/l37/uWMbr8iazatJ06dRq11LGD5Als3Rar2eZvPNjPPvVJI02Wq1967a+2HYW+pDNJtvY2P9+Y++jCAIlgnDB6hWP8bU1J8QhvsZDJ4ymjExODirIsum6ffPotW6jPEtda1NxAzFlZU/JMuexPT0hxnuEjacWdHvP5NG4xp6vR/ONT5tXxYppG0sivauMVth2Ewxir52XOOWy39Dvf52SqUvACU6nZfTaPwOaXraYddVq7dSr7+FMFwCMgaD01hZeS+93otZWvoEU1M3Mj39EYJgP73eC2k2r2AwePZxxSSAgHb7UtrtS3GdqCTpRAnD76x5brijxgGybG6do3ao1a5levrDBME+0vSpNJu/Sbv9eg79eTbcdeJyqtVPMPzQnB7sQ1Eq3U+WTdHvP4Mw/C5ZNkO7/TparV8iz15cW1eJRuOdNBpvJQwfIst2kGXzmF/oRBtbkSKO47OBG4EFYBG4JEmSveMaX9L6DQbfT5rWVi1UZFmNND1j3WOWy3cyN3cxQdAaHelSrd5GpfJ59u2762AH4krlDmZn33TIdVAq7WVu7kL27/80/f4e2u030m6/8Xi+NB2VCYS2B/MLqXjSdDdR9N1Vz2VZ5Si9p1Ydkbm5V1Au//3BJSRR9C3q9auIooRG492HXHc+pVKyZgPuIGhTKn2FxcW9x1Eo0eqmSNMz8w5CE2Qj87Ae74PA9UmSnA1cDxzZ+lbSpup0LmStD6tZFtDpvHKdI2bMzv76YYUHgCBICYJlarX3HLxuZuaqI64balGr/e467ytpgplfSAXTar2JND1yZkKWTdFuX8Z6lxiWy5+jVLr7cT0uIAybTE//MWH4rdF1nyWK7l+zQPFYHCXK5c+tKwZJxTGWIkUcx08C9gC3jA7dAuyJ43j3OMaXdHyybI7l5VtI09rBZCJNp0nTOsvLf0qWza5rvDB8gDBc/c1JEPSpVu8Y/f57hOE/rXEdVCp/s677SppM5hdSMbVav0av92NkWY0sC8iygDSt0+v9II3G29c9XrX6MYKgseq5LAupVP4cgErls4ThyjGNGQS9dcchqRjGtdzjNODbSZIMAJIkGcRx/NDo+MNjuoek49Dr/QiPPPIPVKt/RhTtZTA4i07n1aM1heuVHuP5yhNem2WbvzWZpC3J/EIqpBLLyzdTKn2BSuXjBMGAbvf80Rbfx7PcMDvYV2K1c4/mFFk2TZZFT7jVKAwLFL3eS44jDklFUJjGmQsL6127pnHbvXt9b9V1YpyY5zAL/OZjfzruWzwb2Al8e5VzEWF4wSj+WeD5wF2rXFciDC8q9P9vRY5tUvgMNA7mFsXg93P+Ttwz+NHRL6jVNjLOa4A7gCNnSYQhzM5ewOzsLPCLwAeA1ZuCD9UIgktZWDhrIwGdEH4v5M9nsDWMq0jxIPCUOI6j0VuOCDh1dPyYLC6ukKbZ0S/UCbF79ywPP3wg7zAm3lZ4DpXKuznppDcc1m9iONWzzr59l5Omw/ij6D3Mz//kqMv3o9uAlcmyefbtu+LgdUWzFZ7BduczyF8YBkX5gL+h/MLcIn9+P+dvazyDc5mfP5tS6csEQefg0Sybpt2+kJWV3cAB4ExmZl7F1NSfHbYFapYBlMiyOs3mr9JqXTG6vji2xnPY3nwG+VpPbjGWnhRJknwXuAe4aHToIuDuJEmciiltM93uy1levol+/xyyLCLLSnS7P8H+/Z8nTb/v4HWDwbPYv/+v6HQuJE13kKa7abV+iUceuYs0PTnHr0DSVmF+IU2KiP37P0mr9bpRn4sSabqTRuO3WFm57rArV1bex4EDv0+//3TS9CR6vedw4MANLC7ex+Li/bRaVzLevQEkbbZxLvf4ZeDGOI7fDuwDLhnj2JIKpNs9j273PIbTLUsMe1AcaTD4Zxw48JHNDE3S9mN+IU2EOo3GtTQa1wAtoM7q/S0COp2fp9P5+c0NT9KmGVuRIkmSrwAvGNd4kraCDS1AlaSjMr+QJk0EFGK5maScOBdKkiRJkiQVgkUKSZIkSZJUCBYpJEmSJElSIVikkCRJkiRJhWCRQpIkSZIkFYJFCkmSJEmSVAgWKSRJkiRJUiFYpJAkSZIkSYVgkUKSJEmSJBWCRQpJkiRJklQIFikkSZIkSVIhWKSQJEmSJEmFYJFCkiRJkiQVgkUKSZIkSZJUCBYpJEmSJElSIVikkCRJkiRJhWCRQpIkSZIkFYJFCkmSJEmSVAgWKSRJkiRJUiFYpJAkSZIkSYVgkUKSJEmSJBWCRQpJkiRJklQIFikkSZIkSVIhWKSQJEmSJEmFYJFCkiRJkiQVgkUKSZIkSZJUCBYpJEmSJElSIVikkCRJkiRJhWCRQpIkSZIkFYJFCkmSJEmSVAgWKSRJkiRJUiFYpJAkSZIkSYVgkUKSJEmSJBWCRQpJkiRJklQIFikkSZIkSVIhWKSQJEmSJEmFYJFCkiRJkiQVQmmjA8Rx/AvAlcAzgMuTJLluw1FJkqSJZn4hSdJkGsdMinuA1wI3j2EsSZIkML+QJGkibXgmRZIk9wLEcZxuPBxJkiTzC0mSJtWGixRjEAGEYZB3HBPPZ1AMPof8+Qzy5zPI1yF//1GecWyAuUWB+Bzy5zMoBp9D/nwG+VlPbnHUIkUcx18ETl/j9JOTJBkce2irOgVgx476BofRRi0szOQdgvA5FIHPIH8+g8I4Bfj6iRj4BOcX5hYF4vdz/nwGxeBzyJ/PoBCOmlsctUiRJMmesYWzur8DzgW+A2y04CFJkjYuYphE/N2JusEJzi/MLSRJKpZjzi2KsNyjA/x13kFIkqTDnJAZFJvE3EKSpOI5ptwiyLJsQ3eJ4/gi4FpgB9AFGsB5SZLct6GBJUnSxDK/kCRpMm24SCFJkiRJkjQOYd4BSJIkSZIkgUUKSZIkSZJUEBYpJEmSJElSIVikkCRJkiRJhWCRQpIkSZIkFUIp7wAeFcfxLwBXAs8ALk+S5LqcQ5oYcRyfDdwILACLwCVJkuzNN6rJEcfxe4ALgTOAZydJcm++EU2eOI4XgJuApwEd4GvAv06S5OFcA5tAcRzfDnw/kAIrwK8mSXJPvlFNpjiO3wH8Nlv43yVzi/yYW+TP/CJ/5hfFYG5RHMeaWxRpJsU9wGuBm/MOZAJ9ELg+SZKzgeuBG3KOZ9LcDrwE+GbegUywDHh3kiRxkiTPAb4OXJNzTJPq0iRJfiBJkn8OvAf4o7wDmkRxHO8BXgg8kHcsG2RukR9zi/yZX+TP/KIYzC0KYD25RWGKFEmS3JskyX0MK1zaJHEcPwnYA9wyOnQLsCeO4935RTVZkiT56yRJHsw7jkmWJMkjSZL890MO/S/g+3IKZ6IlSbJ0yB/n8GfCpovjuMrwQ+WbGCbYW5a5RT7MLYrB/CJ/5hfFYG6Rv/XmFoUpUig3pwHfTpJkADD670Oj49LEieM4BH4F+HjesUyqOI4/EsfxA8C7gEvzjmcC/Q7w0SRJ7s87EG1Z5hbS45hf5MvcInfryi02rSdFHMdfBE5f4/STH/1BJkk5ez/D9YquXc9JkiRvAIjj+BeBa4Hz841ocsRx/CLg+cCb847lWJhbSNpCzC9yZG6Rn+PJLTatSJEkyZ7NupfW5UHgKXEcR0mSDOI4joBTR8eliTJqMnYW8PIkSZwKmLMkSW6K4/hDcRwvJEmymHc8E+KHgXOA++M4Bngq8OdxHF+WJMlnco1sFeYWhWVuIR3C/KI4zC1yse7cwuUeEy5Jku8ybCx20ejQRcDddh3WpInj+F3A84ALkiTp5B3PJIrjeCaO49MO+fPLgUdGv7QJkiS5JkmSU5MkOSNJkjOAbwE/VcQChYrL3EJ6jPlFvswt8nc8uUWQZcXoiRXH8UUMp97sALpAAzhv1PBKJ1Acx+cw3CZsB7CP4TZhSb5RTY44jt8HvBI4GfgesJgkyTPzjWqyxHH8TOBe4KtAa3T4/iRJXpFfVJMnjuMnA3cAdWDAMIG4IkmSL+Ya2ASL4/gbwMu26taF5hb5MbfIn/lF/swv8mduUTzHklsUpkghSZIkSZImm8s9JEmSJElSIVikkCRJkiRJhWCRQpIkSZIkFYJFCkmSJEmSVAgWKSRJkiRJUiFYpJAkSZIkSYVgkUKSJEmSJBWCRQpJkiRJklQI/x/yAvr2RCNu4QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_svm(N=10, ax=None):\n",
    "    X, y = make_blobs(n_samples=200, centers=2,\n",
    "                      random_state=0, cluster_std=0.60)\n",
    "    X = X[:N]\n",
    "    y = y[:N]\n",
    "    model = SVC(kernel='linear', C=1E10)\n",
    "    model.fit(X, y)\n",
    "    \n",
    "    ax = ax or plt.gca()\n",
    "    ax.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "    ax.set_xlim(-1, 4)\n",
    "    ax.set_ylim(-1, 6)\n",
    "    plot_svc_decision_function(model, ax)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(16, 6))\n",
    "fig.subplots_adjust(left=0.0625, right=0.95, wspace=0.1)\n",
    "for axi, N in zip(ax, [60, 120]):\n",
    "    plot_svm(N, axi)\n",
    "    axi.set_title('N = {0}'.format(N))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> In the left panel, we see the model and the support vectors for 60 training points.\n",
    "In the right panel, we have doubled the number of training points, but the model has not changed: the three support vectors from the left panel are still the support vectors from the right panel.\n",
    "This insensitivity to the exact behavior of distant points is one of the strengths of the SVM model.\n",
    "\n",
    "左图中，我们看到前60个点生成的模型和支持向量。右图中有两倍数量的训练点，但是模型并未发生变化：左右两图中的三个支持向量是相同的。这种对于远离分隔区域的点的不敏感性是SVM模型的威力所在。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> If you are running this notebook live, you can use IPython's interactive widgets to view this feature of the SVM model interactively:\n",
    "\n",
    "如果你是在notebook中实时运行本节的话，你可以使用IPython的交互组件来动态展示SVM模型特征："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b996275490d9464c85514da643e88979",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='N', options=(10, 200), value=10), Output()), _dom_classes=('widget…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ipywidgets import interact, fixed\n",
    "interact(plot_svm, N=[10, 200], ax=fixed(None));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Beyond linear boundaries: Kernel SVM\n",
    "\n",
    "### 超出线性限制：核SVM\n",
    "\n",
    "> Where SVM becomes extremely powerful is when it is combined with *kernels*.\n",
    "We have seen a version of kernels before, in the basis function regressions of [In Depth: Linear Regression](05.06-Linear-Regression.ipynb).\n",
    "There we projected our data into higher-dimensional space defined by polynomials and Gaussian basis functions, and thereby were able to fit for nonlinear relationships with a linear classifier.\n",
    "\n",
    "当SVM与*核*组合之后，它会变得异常强大。我们前面已经看到一个核的版本，就在[深入：线性回归](05.06-Linear-Regression.ipynb)中介绍过的基本函数回归。那个例子中我们将数据使用多项式和高斯函数投射到高维度空间中，然后就能使用线性分类器来拟合非线性的关系。\n",
    "\n",
    "> In SVM models, we can use a version of the same idea.\n",
    "To motivate the need for kernels, let's look at some data that is not linearly separable:\n",
    "\n",
    "在SVM模型中，我们可以使用相同的思想。为了让我们看到核的作用，使用下面非线性分割的数据："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets.samples_generator import make_circles\n",
    "X, y = make_circles(100, factor=.1, noise=.1)\n",
    "\n",
    "clf = SVC(kernel='linear').fit(X, y)\n",
    "\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "plot_svc_decision_function(clf, plot_support=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> It is clear that no linear discrimination will *ever* be able to separate this data.\n",
    "But we can draw a lesson from the basis function regressions in [In Depth: Linear Regression](05.06-Linear-Regression.ipynb), and think about how we might project the data into a higher dimension such that a linear separator *would* be sufficient.\n",
    "For example, one simple projection we could use would be to compute a *radial basis function* centered on the middle clump:\n",
    "\n",
    "很明显没有线性分类器能够将这些数据点分开。但是我们可以从[深入：线性回归](05.06-Linear-Regression.ipynb)一节中的基本函数回归里面类推过来，同样的将数据投射到更高的维度，然后线性分类器就可以达到划分数据的目标。例如下面使用的以中央的数据群为中心的*径向基函数*："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = np.exp(-(X ** 2).sum(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> We can visualize this extra data dimension using a three-dimensional plot—if you are running this notebook live, you will be able to use the sliders to rotate the plot:\n",
    "\n",
    "可以使用三维图表将这个转换后的数据可视化出来，如果我们使用的是notebook交互模式，甚至还可以使用滑块旋转这个图表："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9767e1e9ccde41bbbf4b46f2ddfc8517",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='elev', options=(-90, 90), value=-90), IntSlider(value=30, descript…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits import mplot3d\n",
    "\n",
    "def plot_3D(elev=30, azim=30, X=X, y=y):\n",
    "    ax = plt.subplot(projection='3d')\n",
    "    ax.scatter3D(X[:, 0], X[:, 1], r, c=y, s=50, cmap='autumn')\n",
    "    ax.view_init(elev=elev, azim=azim)\n",
    "    ax.set_xlabel('x')\n",
    "    ax.set_ylabel('y')\n",
    "    ax.set_zlabel('r')\n",
    "\n",
    "interact(plot_3D, elev=[-90, 90], azip=(-180, 180),\n",
    "         X=fixed(X), y=fixed(y));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> We can see that with this additional dimension, the data becomes trivially linearly separable, by drawing a separating plane at, say, *r*=0.7.\n",
    "\n",
    "然后我们可以看到有了额外的维度后，数据变得线性可分，比方说我们可以在*r*=0.7的位置画出一条分割线。\n",
    "\n",
    "> Here we had to choose and carefully tune our projection: if we had not centered our radial basis function in the right location, we would not have seen such clean, linearly separable results.\n",
    "In general, the need to make such a choice is a problem: we would like to somehow automatically find the best basis functions to use.\n",
    "\n",
    "这个例子中我们需要仔细的选择和调整我们的投射方式：如果我们没有将径向基函数的中心点放置在正确的位置上，就不能找到这样清晰的线性分割线出来。通常这样的选择是一个问题：我们希望有一种自动选择最佳基函数的方法。\n",
    "\n",
    "> One strategy to this end is to compute a basis function centered at *every* point in the dataset, and let the SVM algorithm sift through the results.\n",
    "This type of basis function transformation is known as a *kernel transformation*, as it is based on a similarity relationship (or kernel) between each pair of points.\n",
    "\n",
    "一个实现的方法是在数据集中的*每个*数据点作为中心点计算基函数，然后让SVM算法帮我们从结果中筛选出好的基函数。这种基函数转换被成为*核转换*，因为它建立在每一对数据点之间相似的关系（或称为核）的基础之上。\n",
    "\n",
    "> A potential problem with this strategy—projecting $N$ points into $N$ dimensions—is that it might become very computationally intensive as $N$ grows large.\n",
    "However, because of a neat little procedure known as the [*kernel trick*](https://en.wikipedia.org/wiki/Kernel_trick), a fit on kernel-transformed data can be done implicitly—that is, without ever building the full $N$-dimensional representation of the kernel projection!\n",
    "This kernel trick is built into the SVM, and is one of the reasons the method is so powerful.\n",
    "\n",
    "这种方法的潜在问题是，将$N$个点投射到$N$个维度上是非常消耗计算资源的，特别是$N$增大的情况下。但是因为存在一个被称为[*核技巧*](https://en.wikipedia.org/wiki/Kernel_trick)的过程，在核转换的数据上的拟合可以被隐式完成，也就是说不需要构建完整的$N$为核投射数据就可以完成训练。这个和技巧內建在SVM中，因此是这个算法如此强大的原因之一。\n",
    "\n",
    "> In Scikit-Learn, we can apply kernelized SVM simply by changing our linear kernel to an RBF (radial basis function) kernel, using the ``kernel`` model hyperparameter:\n",
    "\n",
    "在Scikit-Learn中我们要应用核化的SVM，只需要简单将线性的核改为RBF（径向基函数）核，通过设置模型的`kernel`超参数即可："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=1000000.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "    decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
       "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "    tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = SVC(kernel='rbf', C=1E6, gamma='auto')\n",
    "clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "plot_svc_decision_function(clf)\n",
    "plt.scatter(clf.support_vectors_[:, 0], clf.support_vectors_[:, 1],\n",
    "            s=300, lw=1, facecolors='none');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Using this kernelized support vector machine, we learn a suitable nonlinear decision boundary.\n",
    "This kernel transformation strategy is used often in machine learning to turn fast linear methods into fast nonlinear methods, especially for models in which the kernel trick can be used.\n",
    "\n",
    "使用这个核化的支持向量机，我们得到了一条合适的非线性决定边界。这种核转换策略经常在机器学习中被使用在将线性方法转变为快速的非线性方法的场合，特别适合能运用核技巧的模型中。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tuning the SVM: Softening Margins\n",
    "\n",
    "### SVM调优：软化边缘\n",
    "\n",
    "> Our discussion thus far has centered around very clean datasets, in which a perfect decision boundary exists.\n",
    "But what if your data has some amount of overlap?\n",
    "For example, you may have data like this:\n",
    "\n",
    "我们目前讨论集中在非常干净的数据集上，也就是存在着完美的决定边界。如果数据中存在一些重叠的话会怎么样？如下面看到的数据："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, y = make_blobs(n_samples=100, centers=2,\n",
    "                  random_state=0, cluster_std=1.2)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> To handle this case, the SVM implementation has a bit of a fudge-factor which \"softens\" the margin: that is, it allows some of the points to creep into the margin if that allows a better fit.\n",
    "The hardness of the margin is controlled by a tuning parameter, most often known as $C$.\n",
    "For very large $C$, the margin is hard, and points cannot lie in it.\n",
    "For smaller $C$, the margin is softer, and can grow to encompass some points.\n",
    "\n",
    "要处理这种情况，SVM提供了一些附加因素用于*软化边缘*：意思就是，它允许一些数据点潜入到边缘区域，如果这样能达到更好的拟合效果的话。边缘的硬度被一个称为$C$的可调参数控制。如果$C$的值很大，边缘是硬的，也就是数据点无法进入边缘区域。如果$C$的值比较小，边缘是软的，能够蔓延到点之外。\n",
    "\n",
    "> The plot shown below gives a visual picture of how a changing $C$ parameter affects the final fit, via the softening of the margin:\n",
    "\n",
    "下面的图表展示了使用边缘软化技术，调整了$C$参数之后影响到最终拟合的情况："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, y = make_blobs(n_samples=100, centers=2,\n",
    "                  random_state=0, cluster_std=0.8)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(16, 6))\n",
    "fig.subplots_adjust(left=0.0625, right=0.95, wspace=0.1)\n",
    "\n",
    "for axi, C in zip(ax, [10.0, 0.1]):\n",
    "    model = SVC(kernel='linear', C=C).fit(X, y)\n",
    "    axi.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='autumn')\n",
    "    plot_svc_decision_function(model, axi)\n",
    "    axi.scatter(model.support_vectors_[:, 0],\n",
    "                model.support_vectors_[:, 1],\n",
    "                s=300, lw=1, facecolors='none');\n",
    "    axi.set_title('C = {0:.1f}'.format(C), size=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The optimal value of the $C$ parameter will depend on your dataset, and should be tuned using cross-validation or a similar procedure (refer back to [Hyperparameters and Model Validation](05.03-Hyperparameters-and-Model-Validation.ipynb)).\n",
    "\n",
    "最优的$C$值取决于你的数据集，应该通过交叉验证或者简单过程（参见[超参数和模型验证](05.03-Hyperparameters-and-Model-Validation.ipynb)）来调整。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Face Recognition\n",
    "\n",
    "## 例子：人脸识别\n",
    "\n",
    "> As an example of support vector machines in action, let's take a look at the facial recognition problem.\n",
    "We will use the Labeled Faces in the Wild dataset, which consists of several thousand collated photos of various public figures.\n",
    "A fetcher for the dataset is built into Scikit-Learn:\n",
    "\n",
    "作为支持向量机的一个实际例子，让我们来看一下人脸识别问题。我们使用的是一个标注好的数据集，其中包含着几千张公众人物的脸部照片。Scikit-Learn內建了获取数据集的方法："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Ariel Sharon' 'Colin Powell' 'Donald Rumsfeld' 'George W Bush'\n",
      " 'Gerhard Schroeder' 'Hugo Chavez' 'Junichiro Koizumi' 'Tony Blair']\n",
      "(1348, 62, 47)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import fetch_lfw_people\n",
    "faces = fetch_lfw_people(min_faces_per_person=60)\n",
    "print(faces.target_names)\n",
    "print(faces.images.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Let's plot a few of these faces to see what we're working with:\n",
    "\n",
    "我们将其中一些脸谱画出来看一下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(3, 5)\n",
    "for i, axi in enumerate(ax.flat):\n",
    "    axi.imshow(faces.images[i], cmap='bone')\n",
    "    axi.set(xticks=[], yticks=[],\n",
    "            xlabel=faces.target_names[faces.target[i]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Each image contains [62×47] or nearly 3,000 pixels.\n",
    "We could proceed by simply using each pixel value as a feature, but often it is more effective to use some sort of preprocessor to extract more meaningful features; here we will use a principal component analysis (see [In Depth: Principal Component Analysis](05.09-Principal-Component-Analysis.ipynb)) to extract 150 fundamental components to feed into our support vector machine classifier.\n",
    "We can do this most straightforwardly by packaging the preprocessor and the classifier into a single pipeline:\n",
    "\n",
    "每张图像含有[62×47]或者说将近3000像素点。我们可以使用每个像素点作为数据集的一个特征，但是通常来说更有效的做法是采用一些预处理器来提取图像中有意义的特征；这里我们将采用主成分分析（参见[深入：主成分分析](05.09-Principal-Component-Analysis.ipynb)）来提取图像中150个基础成分，然后输入到支持向量机分类器中。最简单完成这项任务的方式是将预处理器和分类器连接成一个管道："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.decomposition import PCA as RandomizedPCA\n",
    "from sklearn.pipeline import make_pipeline\n",
    "\n",
    "pca = RandomizedPCA(n_components=150, whiten=True, random_state=42)\n",
    "svc = SVC(kernel='rbf', class_weight='balanced')\n",
    "model = make_pipeline(pca, svc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> For the sake of testing our classifier output, we will split the data into a training and testing set:\n",
    "\n",
    "为了验证我们分类器的性能，我们将数据分成训练集和测试集："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "Xtrain, Xtest, ytrain, ytest = train_test_split(faces.data, faces.target,\n",
    "                                                random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Finally, we can use a grid search cross-validation to explore combinations of parameters.\n",
    "Here we will adjust ``C`` (which controls the margin hardness) and ``gamma`` (which controls the size of the radial basis function kernel), and determine the best model:\n",
    "\n",
    "最后，我们可以使用网格查找交叉验证来验证我们的模型超参数的组合。这里我们会调整`C`（用来控制边缘硬度）和`gamma`（用来控制径向基函数核的大小），然后找到最佳模型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 32s, sys: 919 ms, total: 1min 33s\n",
      "Wall time: 31.4 s\n",
      "{'svc__C': 10, 'svc__gamma': 0.001}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "param_grid = {'svc__C': [1, 5, 10, 50],\n",
    "              'svc__gamma': [0.0001, 0.0005, 0.001, 0.005]}\n",
    "grid = GridSearchCV(model, param_grid, cv=3)\n",
    "\n",
    "%time grid.fit(Xtrain, ytrain)\n",
    "print(grid.best_params_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The optimal values fall toward the middle of our grid; if they fell at the edges, we would want to expand the grid to make sure we have found the true optimum.\n",
    "\n",
    "最优值应该落在网格的中央位置；如果它们落在边缘位置，我们应该考虑扩大网格来确保我们找到了最优值。\n",
    "\n",
    "> Now with this cross-validated model, we can predict the labels for the test data, which the model has not yet seen:\n",
    "\n",
    "现在我们有了经过交叉验证后的模型，可以用来预测测试数据上的标签了，这些数据模型都没有接触过："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = grid.best_estimator_\n",
    "yfit = model.predict(Xtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Let's take a look at a few of the test images along with their predicted values:\n",
    "\n",
    "下面我们看一下测试照片以及它们对应的预测标签值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 24 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(4, 6)\n",
    "for i, axi in enumerate(ax.flat):\n",
    "    axi.imshow(Xtest[i].reshape(62, 47), cmap='bone')\n",
    "    axi.set(xticks=[], yticks=[])\n",
    "    axi.set_ylabel(faces.target_names[yfit[i]].split()[-1],\n",
    "                   color='black' if yfit[i] == ytest[i] else 'red')\n",
    "fig.suptitle('Predicted Names; Incorrect Labels in Red', size=14);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Out of this small sample, our optimal estimator mislabeled only a single face (Bush’s\n",
    "face in the bottom row was mislabeled as Blair).\n",
    "We can get a better sense of our estimator's performance using the classification report, which lists recovery statistics label by label:\n",
    "\n",
    "在这个小样本中，我们优化过的评估器仅标错了一个人的脸（最下面一行布什的脸被错误的标记成了布莱尔）。我们可以使用分类报告更好的得到评估器的性能估计，报告中我们对每个标签都进验证得出统计数据："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   precision    recall  f1-score   support\n",
      "\n",
      "     Ariel Sharon       0.65      0.73      0.69        15\n",
      "     Colin Powell       0.80      0.87      0.83        68\n",
      "  Donald Rumsfeld       0.74      0.84      0.79        31\n",
      "    George W Bush       0.92      0.83      0.88       126\n",
      "Gerhard Schroeder       0.86      0.83      0.84        23\n",
      "      Hugo Chavez       0.93      0.70      0.80        20\n",
      "Junichiro Koizumi       0.92      1.00      0.96        12\n",
      "       Tony Blair       0.85      0.95      0.90        42\n",
      "\n",
      "         accuracy                           0.85       337\n",
      "        macro avg       0.83      0.84      0.84       337\n",
      "     weighted avg       0.86      0.85      0.85       337\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(ytest, yfit,\n",
    "                            target_names=faces.target_names))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> We might also display the confusion matrix between these classes:\n",
    "\n",
    "当然我们也可以绘制这些分类之间的粗混淆矩阵："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "mat = confusion_matrix(ytest, yfit)\n",
    "sns.heatmap(mat.T, square=True, annot=True, fmt='d', cbar=False,\n",
    "            xticklabels=faces.target_names,\n",
    "            yticklabels=faces.target_names)\n",
    "plt.xlabel('true label')\n",
    "plt.ylabel('predicted label');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This helps us get a sense of which labels are likely to be confused by the estimator.\n",
    "\n",
    "上面的矩阵能帮助我们建立评估器在每个标签上性能的直观印象。\n",
    "\n",
    "> For a real-world facial recognition task, in which the photos do not come pre-cropped into nice grids, the only difference in the facial classification scheme is the feature selection: you would need to use a more sophisticated algorithm to find the faces, and extract features that are independent of the pixellation.\n",
    "For this kind of application, one good option is to make use of [OpenCV](http://opencv.org), which, among other things, includes pre-trained implementations of state-of-the-art feature extraction tools for images in general and faces in particular.\n",
    "\n",
    "在真实的人脸识别任务中，人脸的照片并没有预先裁剪成一个网格，与例子中的唯一区别在于特征选择部分：你可能需要使用一个复杂得多的算法来找到人脸，并将其中像素中独立的特征提取出来。对于这类应用，[OpenCV](http://opencv.org)是一个很好的选择，因为它其中已经內建了预训练的特征提取工具实现，无论是通用的图像还是人脸的照片。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Support Vector Machine Summary\n",
    "\n",
    "## 支持向量机总结\n",
    "\n",
    "> We have seen here a brief intuitive introduction to the principals behind support vector machines.\n",
    "These methods are a powerful classification method for a number of reasons:\n",
    "\n",
    "> - Their dependence on relatively few support vectors means that they are very compact models, and take up very little memory.\n",
    "- Once the model is trained, the prediction phase is very fast.\n",
    "- Because they are affected only by points near the margin, they work well with high-dimensional data—even data with more dimensions than samples, which is a challenging regime for other algorithms.\n",
    "- Their integration with kernel methods makes them very versatile, able to adapt to many types of data.\n",
    "\n",
    "本节内容对支持向量机背后的原理进行了简要直观的介绍。这些方法在分类任务中非常强大的原因在于：\n",
    "\n",
    "- 它们仅依赖于很少的支持向量，这意味着它们是非常紧凑的模型，占用的内存也非常少。\n",
    "- 一旦模型训练好了，预测阶段非常快速。\n",
    "- 因为它们仅受到边缘区域附近数据点的影响，所以它们在高维度数据上也工作良好，甚至数据的特征维度比样本数还多的情况下。这对于其他算法来说都是一个具挑战性的领域。\n",
    "- 将它们与核方法集成之后将会非常灵活强大，能够使用多种类型的数据。\n",
    "\n",
    "> However, SVMs have several disadvantages as well:\n",
    "\n",
    "> - The scaling with the number of samples $N$ is $\\mathcal{O}[N^3]$ at worst, or $\\mathcal{O}[N^2]$ for efficient implementations. For large numbers of training samples, this computational cost can be prohibitive.\n",
    "- The results are strongly dependent on a suitable choice for the softening parameter $C$. This must be carefully chosen via cross-validation, which can be expensive as datasets grow in size.\n",
    "- The results do not have a direct probabilistic interpretation. This can be estimated via an internal cross-validation (see the ``probability`` parameter of ``SVC``), but this extra estimation is costly.\n",
    "\n",
    "当然，SVM也有如下一些缺点：\n",
    "\n",
    "- 算法复杂度在样本数为$N$的情况下，最差是$\\mathcal{O}[N^3]$，最好实现是$\\mathcal{O}[N^2]$。这导致训练集特别大的情况下，这个计算代价是无法承受的。\n",
    "- 算法的性能结果很大程度上依赖于边缘软化参数$C$的选择。这需要通过交叉验证来小心选择，在数据集增大时该操作也是非常昂贵的。\n",
    "- 结果没有直接的概率解释。虽然可以通过内部的交叉验证（参见`SVC`分类器的`probability`参数）来估计，但是要更精确的估算是困难的。\n",
    "\n",
    "> With those traits in mind, I generally only turn to SVMs once other simpler, faster, and less tuning-intensive methods have been shown to be insufficient for my needs.\n",
    "Nevertheless, if you have the CPU cycles to commit to training and cross-validating an SVM on your data, the method can lead to excellent results.\n",
    "\n",
    "有了上面的特性，作者通过仅会在其他简单快速和更少超参调节的方法无法满足的情况下采用SVM。然而，如果你有很好的计算资源来完成SVM的训练和交叉验证的话，这个方法能提供优异的结果。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [In Depth: Linear Regression](05.06-Linear-Regression.ipynb) | [Contents](Index.ipynb) | [In-Depth: Decision Trees and Random Forests](05.08-Random-Forests.ipynb) >\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.07-Support-Vector-Machines.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open and Execute in Google Colaboratory\"></a>\n"
   ]
  }
 ],
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